SlideShare una empresa de Scribd logo
1 de 58
Descargar para leer sin conexión
Gs08 modernize your data platform with sql technologies   wash dc
bobward@microsoft.com
slideshare.net
github
• Disparate systems and processes
• Multiple tools and skillsets
• High cost of ownership
• Siloed insights on disconnected data
• Costly data movement and delay
Challenges of the Modern Data Platform
Fragmented architectures are inefficient
AnalyticsVisualization
Relational in the cloud
Analytics Visualization
Hadoop
{ }
NoSQL Data Lake
AnalyticsVisualization
Relational DBAppliance
Analytics Visualization
Hadoop Appliance
CloudOn-premises
Relational Non-relational
Azure SQL Database
Azure SQL Data Warehouse
SQL Server 2016 on VM
Analytics Platform System
Azure Data Lake
SQL Server 2016
Analytics Platform System
SQL
Relational Non-relational
On-premisesCloudMicrosoft Data Platform
Transforming data into intelligent action
• Manage all your data in a mission critical,
scalable, secure way
• Gain deep insights across all of your data
without data movement
• Utilize existing skills and investments
• Consistent on-premises, cloud and hybrid
experiences
Federated query
Business intelligence
Machine learning &
advanced analytics
Insights
Consistent experience is everything
Gs08 modernize your data platform with sql technologies   wash dc
Continuous Innovation
End-to-end mobile BI
Advanced Analytics
Enterprise-grade DW
Mission critical OLTP
The best
SQL Server
release in history
SQL Server 2016
Speed
Agility
Proven
Feedback
SQL DB SQL DB SQL DB SQL DB
New innovations
Across customer base
Cloud-First Approach + DevOps
Continuous
enhancements
Hybridcloud
National Institute of Standards and Technology Comprehensive Vulnerability Database update 12/2016.
Everything built-inTPC-H
Oracle
is #5#2
SQL Server
#1
SQL Server
#3
SQL Server
The Power of SQL Server
Everything built-in
June 2016
SQL Server 2016
TPC-E
0 1
4
0 0
3
0
34
29
22
15
5
22
16
6
43
20
69
18
49
74
3
0
10
20
30
40
50
60
70
80
2010 2011 2012 2013 2014 2015 2016
SQL Server Oracle MySQL2 SAP HANA
1/12
Only data solution to
encrypt your data at
rest and in motion
Connect your
relational data to
big data with PolyBase
Real-time operational
analytics without
impacting performance
Up to 30x faster
transactions, 100x faster
queries with InMemory
Unparalleled choice
for developer tools
and languages
1 T-SQL
Java
C/C++
C#/VB.NET
PHP
Node.js
Python
Ruby
For all your applications
Innovations across all editions
Available now
SQL Server 2016 SP1
On the platform of your choice
SQL Server v.Next
Targeting CY2017
SQL Server v.Next GA*
SQL Server v.Next Public Preview available now on Linux, Windows, and Docker.
Just Runs Faster
Core Engine Scalability
Automatic Soft NUMA
Dynamic Memory Objects
SOS_RWLock
Fair and Balanced Scheduling
Parallel INSERT..SELECT
Parallel Redo
DBCC
DBCC Scalability
DBCC Extended Checks
TempDB
Goodbye Trace Flags
Setup and Automatic Configuration of Files
Optimistic Latching
I/O
Instant File Initialization is No Longer Hidden
Multiple Log Writers
Indirect Checkpoint Default Just Makes Sense
Log I/O at the Speed of Memory
Spatial
Native Implementations
TVP and Index Improvements
Columnstore
Batch Mode and Window Functions
Always On Availability Groups
Turbocharged
Better Compression and Encryption
Persisted Log Buffer
The evolution of storage
HDD  SSD (ms)
PCI NVMe SSD (μs)
Tired of WRITELOG waits?
Along comes NVDIMM(ns)
Windows Server 2016 supports block storage
(standard I/O path)
A new interface for DirectAccess (DAX) Persistent
Memory
(PM)
Watch these
videos
Channel 9 on
SQL and PMM
NVDIMM on
Win 2016 from
build
Format your NTFS
volume with /dax
on Windows
Server 2016
Create a 2nd tlog
file on this new
volume on SQL
Server 2016 SP1
Tail of the log is
now a “memcpy”
so commit is fast
WRITELOG waits =
0 ms
here
Mission critical platform Deeper Insights Hyperscale
In-Memory OLTP
Greater T-SQL surface area, terabytes of
memory supported, and higher number of
parallel CPUs
Query Store
A flight data recorder for your database
Always Encrypted
Sensitive data remains encrypted at all times,
with ability to query
Row-Level Security
Fine-grained access control for table rows
Enhanced Always On
Distributed Availability Groups, Basic
Availability Groups, Automatic Failover
The richest set of diagnostics in the
industry. Read more here
High-Performance Execution Engines
ColumnStore + Batch
Mode Execution
• Columnar compression to save
space in memory and on disk
• New execution engine that
optimizes instructions/row and
minimizes CPU data bus I/O stalls
• Often gives speedups of 10x
• Allows you to store, manage, and
gain value out of significantly more
data
In-Memory OLTP Engine
Model
• Lock-free algorithms
• Optimistic concurrency model
• Full transactional support
• Compiled procedures
• Can give significant speedups (2x-
50x) on high-end OLTP applications
Capturing technical breakthroughs in two areas
These enable you to write SQL and leverage ever-
increasing performance for your applications
MissionCriticalPlatform
Gs08 modernize your data platform with sql technologies   wash dc
Secure Code
• Secure development lifecycle
• Least vulnerable last 6 years
Most Secure Database
Secure engine
Least vulnerable last 6 years
0 2
11
8
0 1
4
0 0
3
69
53 53 55
34
29
22
15
5
22
5
28
25
29
21
6
13
3
0
6
16 16
9 8 6
43
20
69
18
49
3
0
10
20
30
40
50
60
70
80
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
SQL Server Oracle DB2 MySQL SAP HANA
* National Institute of Standards and Technology Comprehensive
Vulnerability Database update 10/2015
while being most utilized
MissionCriticalPlatform
Most Secure Database
Surrounded by layers of protection
Secure Code
• Secure development lifecycle
• Least vulnerable last 6 years
• SQL Threat Detection
• SQL Server Auditing
• Row-level Security
• Dynamic Data Masking
• Always Encrypted
• Transparent Data Encryption
• Encryption-in-flight
Control Access
• SQL Authentication
• Windows Authentication
• Azure Active Directory Auth.
Monitor activity
Control access
Protect data
Come to the instructor lead
security lab at 4:45 pm today!
MissionCriticalPlatform
trust boundary
"SELECT Name FROM Customers
WHERE SSN = @SSN","111-22-3333"
Always Encrypted
Protect data at rest and in motion, on-premises and in the cloud
Name
Wayne Jefferson
ADO .NET
Name
0x19ca706fbd9a
Result SetResult Set
Client
Name SSN Country
0x19ca706fbd9a 0x7ff654ae6d USA
SQL Server or SQL Database
"SELECT Name FROM Customers
WHERE SSN = @SSN",0x7ff654ae6d
ciphertext
Encrypted sensitive data and corresponding keys
are never seen in plaintext in SQL Server
dbo.Customers
ciphertext
Security
MissionCriticalPlatform
Optimizing query performance and costs
Query Store = flight data recorder for databases
Built-in query monitoring
• Negligible perf & storage overhead
• Survives failover, memory pressure, …
• Data ready when that incident happens
T-SQL interface and SSMS UX
Top insights into your workload
• Query and resource stats
• Query plans
Developer
App User
Azure
application On-premise
Developer needs to find and fix
the underlying problem, ASAP
Customer reports the issue
(app is slow/unresponsive)
MissionCriticalPlatform
Gs08 modernize your data platform with sql technologies   wash dc
Improved Always On Availability Groups
• 3 Replicas for Automatic Failover
• Database Failure Detection
Higher
Availability
• Support for Column-store Indexes
• Load Balancing of Read Workloads
More Powerful
Readable
Secondaries
• 4X Synchronization ThroughputScalability
• Different Windows Clusters
• Different Windows Domains
Flexibility
• Basic Availability Groups in
Standard Edition
Licensing
Always On Turbocharged
MissionCriticalPlatform
Mission critical platform Deeper Insights Hyperscale
Real-time operational analytics
Running of analytical workloads concurrently
with OLTP workloads
R Integration
Insights from data across SQL Server and
Hadoop with the simplicity of T-SQL
PolyBase
Insights from data across SQL Server and
Hadoop with the simplicity of T-SQL
Mobile BI
Mobile reports on SSRS with Mobile Report
Publisher
Temporal Tables, JSON
Track change history, integrate with modern
service easily
0100101010110 SQL Server
OLTP
SQL Server
data warehouse
ETL
In-memory
ColumnStore
In-memory
OLTP
Real-time fraud
detection
Operational analytics
Single system for OLTP and real-time analytics
Fraud detected
2-24
hrs
DeeperInsights
Data Scientist
Interact directly with data
Built-in to SQL Server
Data Developer/DBA
Manage data and
analytics together
Built-in advanced analytics
Running R algorithms at massive data scale
Example Solutions
• Salesforecasting
• Warehouse efficiency
• Predictive maintenance
Relational Data
Analytic Library
T-SQL Interface
Extensibility
?
R
RIntegration
010010
100100
010101
Microsoft Azure
Marketplace
New R scripts
010010
100100
010101
010010
100100
010101
010010
100100
010101
010010
100100
010101
010010
100100
010101
• Credit risk protection
DeeperInsights
PolyBase
Query relational and non-relational data with T-SQL
T-SQL query
SQL Server Hadoop
Quote:
************************
**********************
*********************
**********************
***********************
$658.39
Jim Gray
Name
11/13/58
DOB
WA
State
Ann Smith 04/29/76 ME
DeeperInsights
Support for Temporal Data
Track historical data
DeeperInsights
• Data changes over time (!)
• Databases naturally provide
a current view
• But an historical perspective
is often critical
Time travel
Data audit
Predictive analytics
Repair record-level corruptions
Gs08 modernize your data platform with sql technologies   wash dc
Mission critical platform Deeper Insights Hyperscale
Stretch Database
Stretch operational tables in a secure manner
into Azure for cost-effective historic data
availability.
Enhanced backup to Azure
Faster restore times, 50% reduction in storage.
Larger DBs
Order history
Name SSN Date
Jane Doe cm61ba906fd 2/28/2005
Jim Gray ox7ff654ae6d 3/18/2005
John Smith i2y36cg776rg 4/10/2005
Bill Brown nx290pldo90l 4/27/2005
Sue Daniels ypo85ba616rj 5/12/2005
Sarah Jones bns51ra806fd 5/22/2005
Jake Marks mci12hh906fj 6/07/2005
Order history
Name SSN Date
Jane Doe cm61ba906fd 2/28/2005
Jim Gray ox7ff654ae6d 3/18/2005
John Smith i2y36cg776rg 4/10/2005
Bill Brown nx290pldo90l 4/27/2005
Customer data
Product data
Order History
Stretch to cloud
Stretch SQL Server into Azure
Stretch cold data to Azure with remote query processing
App
Query
Microsoft Azure

Jim Gray ox7ff654ae6d 3/18/2005
HyperscaleCloud
Azure
SQL Virtual
Machines
Azure
SQL Database
Azure
SQL Data
Warehouse
Fully managed Database Service …
So you can focus on your Business
• Built for SaaS and Enterprise applications
• Predictable performance & Pricing
• Elastic database pool for unpredictable SaaS workloads
• 99.99% availability built-in
• Geo-replication and restore services for data protection
• Secure and compliant for your sensitive data
• Fully compatible with SQL Server 2016 databases
Predictable workloads
Single databases or partitioned data across multiple
databases; scale between service tiers and
performance levels as capacity needs fluctuate.
Scaledatabases
upasneeded
Scale out/in the pool
…
Single database or
partitioned databases
Customer
1
Customer
2
Customer
3 Customer
#N…
Unpredictable workloads
For large numbers of databases with unpredictable
performance demands; pool resources to be shared
between these databases.
Elastic Database Pool
Databasesconsume
resourcesasneeded
Managing large numbers of Databases
SQL Database Service Tiers (single DB model)
*The 99.99% availability SLA does not apply to the existing Web and Business editions, which will continue to be supported at 99.9% availability.
Built For
Available SLA
Database Max Size
Business Continuity
Security
Performance Objectives
Database Transaction
Units (DTUs)
Available Tiers
($/Month) and GA Price
Point-in-time Restore
(“oops” Recovery)
BASIC PREMIUMSTANDARD
P1S0
Light transactional workloads Medium transactional workloads Heavy Transactional Workloads
99.99%*
2 GB 250 GB 500 – 1,000 GB (more soon)
Any point within 7 days Any point within 14 days Any point within 35 days
Geo-restore
Geo-replication, standby
secondary
Active geo-replication, up to four readable
secondary backups
Auditing, row-level security, dynamic data masking, encryption
Transactions per hour Transactions per minute Transactions per second
5
$4.99
S1 S2 S3 P2 P4 P6 P11
10 20 50 100
$15 $30 $75 $150
125 250 500 1,000 1,750
$465 $930 $1,860 $3,720 $7,001
P15 …
4,000
$16,003
Azure SQL Data Warehouse
• A relational data-warehouse-as-a-service, fully managed by Microsoft.
• Industries first elastic cloud data warehouse with proven SQL Server capabilities.
• Support your smallest to your largest data storage needs.
Saas
Azure
Public
Cloud
Office 365Office 365
AzureAzure
Gs08 modernize your data platform with sql technologies   wash dc
Source
Target
Windows Azure
Windows Azure
Tool(s) DMA DMA SSMA
Legacy
Modern
Comparison
Reports
A’
SQL 2008 Instance
Extensive
tracing
Statistical
Analysis
Analyze
Results
B
SQL 2016 Instance
Extensive
tracing
capture prod
workload
Migrations by Industry
Financial Services 139
Discrete Manufacturing 122
Retail &
Consumer Goods
113
Government 105
Health 94
Professional Services 93
Process Manufacturing
& Resources
59
Hospitality & Travel 44
Telecommunications 36
Power & Utilities 31
Other Industries 119
TOTAL 955
Azure SQL Database
Azure SQL Data Warehouse
SQL Server 2016 on VM
Analytics Platform System
Azure Data Lake
SQL Server 2016
Analytics Platform System
SQL
Relational Non-relational
On-premisesCloudMicrosoft Data Platform
Transforming data into intelligent action
• Manage all your data in a mission critical,
scalable, secure way
• Gain deep insights across all of your data
without data movement
• Utilize existing skills and investments
• Consistent on-premises, cloud and hybrid
experiences
Federated query
Business intelligence
Machine learning &
advanced analytics
Insights
Page
Free E-Book
Blog
Blog
Blog Series
bobward@microsoft.com
Gs08 modernize your data platform with sql technologies   wash dc
Gs08 modernize your data platform with sql technologies   wash dc
Industry Observations
In-Memory Transactional Processing
SQL Server Integration
• Same manageability,
administration &
development experience
• Integrated queries &
transactions
• Integrated HA and
backup/restore
In-Memory Data
Access
• Indexes (hash and range)
exist only in memory
• Records exist only in
memory (pointers from
indexes)
• No buffer pool, B-trees
• Stream-based storage
T-SQL Compiled to
Machine Code
• T-SQL compiled to machine
code via C code generator
• Invoking a procedure is just
a DLL entry-point
• Aggressive optimizations @
compile-time
Declining memory price Many-core processorsStalling CPU clock rate Lower TCO
Hardware trends Business
Integrated experience
High performance data
operations
Efficient business-logic
processing
Customer
Benefits
ArchitecturalPillarsDrivers
High Concurrency
• Core engine uses lock-free
algorithms
• No lock manager, latches or
spinlocks
• Multi-version optimistic
concurrency control with full
ACID support
Frictionless scale-up
45
Column-Store Indexes
Improved compression:
Data from same domain
compress better
Reduced I/O:
Fetch only columns needed
…
Row-store indexes Column-store indexes
Ideal for OLTP
Efficient operation on small set of rows
C5C1 C2 C3 C4
Improved Performance:
More data fits in memory
Optimized for CPU utilization
Ideal for DW Workload
Benefits of Column-Store Indexes
Gs08 modernize your data platform with sql technologies   wash dc
Time TravelData Audit
Row-level error
correction
• Interchange data with apps
and services
• Exploit agility of NoSQL to
easily extend your app
SQL Server
Web app, service
CREATE TABLE Departments
(
DeptId int NOT NULL PRIMARY KEY CLUSTERED
, DeptName varchar(50) NOT NULL
, ManagerId int NULL
)
;
How Temporal Tables Work
End-to-endmobileBI
CREATE TABLE Departments
(
DeptId int NOT NULL PRIMARY KEY CLUSTERED
, DeptName varchar(50) NOT NULL
, ManagerId int NULL
, SysStartTime datetime2 GENERATED ALWAYS AS ROW START NOT NULL
, SysEndTime datetime2 GENERATED ALWAYS AS ROW END NOT NULL
, PERIOD FOR SYSTEM_TIME (SysStartTime, SysEndTime)
)
WITH (SYSTEM_VERSIONING = ON (HISTORY_TABLE = DepartmentHistory))
;
How Temporal Tables Work
End-to-endmobileBI
How Temporal Tables Work
Insert
prior version Start EndDeptId DeptName ManagerId
DepartmentsHistory
End-to-endmobileBI
Update / Delete
Departments (temporal)
Departments
Start EndDeptId DeptName ManagerId
How Temporal Tables Work
Start EndDeptId DeptName ManagerId
DepartmentsHistory
End-to-endmobileBI
Normal query
SELECT * FROM Departments
GO
Departments (temporal)
Departments
Start EndDeptId DeptName ManagerId
How Temporal Tables Work
Start EndDeptId DeptName ManagerId
Departments DepartmentsHistory
End-to-endmobileBI
Temporal query SELECT * FROM Departments
FOR SYSTEM_TIME AS OF '2015.01.01'
GO
Departments (temporal)
Start EndDeptId DeptName ManagerId
Paginated reports
Design beautiful documents using updated
tools and new features
Mobile reports
Create responsive, interactive reports optimized
for mobile devices
Modern web portal
Consume both types of reports in one web
portal using modern browsers
SQL Server Reporting Services
SQL Server Analysis Services 2016
Easily create models
IT pro
Increase adoption
Business analyst
Share insights faster
Faster time
to insight
BI consumers
Gs08 modernize your data platform with sql technologies   wash dc
OLTP
Industry leading TCO
$648K
+ $120
per user for Power BI
SQL Server 2016
ADVANCED ANALYTICS
BUSINESS INTELLIGENCE
OLTP
DATA WAREHOUSING
3.4x
20x
per user
$2.2M
+ $2,230
per user for BI
Note: For OLTP and DW scenario, the price comparison
is based on a server with 2 proc, 8 cores each
Built-in with SQL Server vs.
expensive add-ons with Oracle
Complete mobile BI
In-memory
End-to-end security
Advanced Analytics
built-in
built-in
built-in
built-in
DATA WAREHOUSING
BUSINESS INTELLIGENCE
ADVANCED ANALYTICS
Easy with SQL Server migration assistants
SSMA for Oracle
SSMA for Sybase
SSMA for DB2
SSMA for MySQL
SSMA for Access

Más contenido relacionado

La actualidad más candente

SQL Server 2017 Deep Dive - @Ignite 2017
SQL Server 2017 Deep Dive - @Ignite 2017SQL Server 2017 Deep Dive - @Ignite 2017
SQL Server 2017 Deep Dive - @Ignite 2017Travis Wright
 
C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...
C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...
C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...DataStax Academy
 
The Roadmap for SQL Server 2019
The Roadmap for SQL Server 2019The Roadmap for SQL Server 2019
The Roadmap for SQL Server 2019Amit Banerjee
 
Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...
Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...
Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...DataStax
 
Introducing Azure SQL Data Warehouse
Introducing Azure SQL Data WarehouseIntroducing Azure SQL Data Warehouse
Introducing Azure SQL Data WarehouseGrant Fritchey
 
Hadoop for the Absolute Beginner
Hadoop for the Absolute BeginnerHadoop for the Absolute Beginner
Hadoop for the Absolute BeginnerIke Ellis
 
Migration From Oracle to PostgreSQL
Migration From Oracle to PostgreSQLMigration From Oracle to PostgreSQL
Migration From Oracle to PostgreSQLPGConf APAC
 
Blockchain for the DBA and Data Professional
Blockchain for the DBA and Data ProfessionalBlockchain for the DBA and Data Professional
Blockchain for the DBA and Data ProfessionalKaren Lopez
 
Azure data bricks by Eugene Polonichko
Azure data bricks by Eugene PolonichkoAzure data bricks by Eugene Polonichko
Azure data bricks by Eugene PolonichkoAlex Tumanoff
 
Azure Databricks is Easier Than You Think
Azure Databricks is Easier Than You ThinkAzure Databricks is Easier Than You Think
Azure Databricks is Easier Than You ThinkIke Ellis
 
Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...
Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...
Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...Data Con LA
 
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...DataStax
 
SQL Server 2017 Machine Learning Services
SQL Server 2017 Machine Learning ServicesSQL Server 2017 Machine Learning Services
SQL Server 2017 Machine Learning ServicesSorin Peste
 
Powering Interactive Data Analysis at Pinterest by Amazon Redshift
Powering Interactive Data Analysis at Pinterest by Amazon RedshiftPowering Interactive Data Analysis at Pinterest by Amazon Redshift
Powering Interactive Data Analysis at Pinterest by Amazon RedshiftJie Li
 
Stumbling stones when migrating from Oracle
 Stumbling stones when migrating from Oracle Stumbling stones when migrating from Oracle
Stumbling stones when migrating from OracleEDB
 
Powering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta LakePowering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta LakeDatabricks
 
Azure + DataStax Enterprise (DSE) Powers Office365 Per User Store
Azure + DataStax Enterprise (DSE) Powers Office365 Per User StoreAzure + DataStax Enterprise (DSE) Powers Office365 Per User Store
Azure + DataStax Enterprise (DSE) Powers Office365 Per User StoreDataStax Academy
 
Discovery Day 2019 Sofia - Big data clusters
Discovery Day 2019 Sofia - Big data clustersDiscovery Day 2019 Sofia - Big data clusters
Discovery Day 2019 Sofia - Big data clustersIvan Donev
 
DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016
DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016
DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016DataStax
 

La actualidad más candente (20)

SQL Server 2017 Deep Dive - @Ignite 2017
SQL Server 2017 Deep Dive - @Ignite 2017SQL Server 2017 Deep Dive - @Ignite 2017
SQL Server 2017 Deep Dive - @Ignite 2017
 
What database
What databaseWhat database
What database
 
C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...
C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...
C* Summit 2013: Searching for a Needle in a Big Data Haystack by Jason Ruther...
 
The Roadmap for SQL Server 2019
The Roadmap for SQL Server 2019The Roadmap for SQL Server 2019
The Roadmap for SQL Server 2019
 
Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...
Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...
Cold Storage That Isn't Glacial (Joshua Hollander, Protectwise) | Cassandra S...
 
Introducing Azure SQL Data Warehouse
Introducing Azure SQL Data WarehouseIntroducing Azure SQL Data Warehouse
Introducing Azure SQL Data Warehouse
 
Hadoop for the Absolute Beginner
Hadoop for the Absolute BeginnerHadoop for the Absolute Beginner
Hadoop for the Absolute Beginner
 
Migration From Oracle to PostgreSQL
Migration From Oracle to PostgreSQLMigration From Oracle to PostgreSQL
Migration From Oracle to PostgreSQL
 
Blockchain for the DBA and Data Professional
Blockchain for the DBA and Data ProfessionalBlockchain for the DBA and Data Professional
Blockchain for the DBA and Data Professional
 
Azure data bricks by Eugene Polonichko
Azure data bricks by Eugene PolonichkoAzure data bricks by Eugene Polonichko
Azure data bricks by Eugene Polonichko
 
Azure Databricks is Easier Than You Think
Azure Databricks is Easier Than You ThinkAzure Databricks is Easier Than You Think
Azure Databricks is Easier Than You Think
 
Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...
Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...
Big Data Day LA 2015 - Introducing N1QL: SQL for Documents by Jeff Morris of ...
 
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
 
SQL Server 2017 Machine Learning Services
SQL Server 2017 Machine Learning ServicesSQL Server 2017 Machine Learning Services
SQL Server 2017 Machine Learning Services
 
Powering Interactive Data Analysis at Pinterest by Amazon Redshift
Powering Interactive Data Analysis at Pinterest by Amazon RedshiftPowering Interactive Data Analysis at Pinterest by Amazon Redshift
Powering Interactive Data Analysis at Pinterest by Amazon Redshift
 
Stumbling stones when migrating from Oracle
 Stumbling stones when migrating from Oracle Stumbling stones when migrating from Oracle
Stumbling stones when migrating from Oracle
 
Powering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta LakePowering Interactive BI Analytics with Presto and Delta Lake
Powering Interactive BI Analytics with Presto and Delta Lake
 
Azure + DataStax Enterprise (DSE) Powers Office365 Per User Store
Azure + DataStax Enterprise (DSE) Powers Office365 Per User StoreAzure + DataStax Enterprise (DSE) Powers Office365 Per User Store
Azure + DataStax Enterprise (DSE) Powers Office365 Per User Store
 
Discovery Day 2019 Sofia - Big data clusters
Discovery Day 2019 Sofia - Big data clustersDiscovery Day 2019 Sofia - Big data clusters
Discovery Day 2019 Sofia - Big data clusters
 
DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016
DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016
DataStax | DataStax Tools for Developers (Alex Popescu) | Cassandra Summit 2016
 

Destacado

Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Lucas Jellema
 
2017 iosco research report on financial technologies (fintech)
2017 iosco research report on  financial technologies (fintech)2017 iosco research report on  financial technologies (fintech)
2017 iosco research report on financial technologies (fintech)Ian Beckett
 
2015 Internet Trends Report
2015 Internet Trends Report2015 Internet Trends Report
2015 Internet Trends ReportIQbal KHan
 
Tracxn Research - Healthcare Analytics Landscape, February 2017
Tracxn Research - Healthcare Analytics Landscape, February 2017Tracxn Research - Healthcare Analytics Landscape, February 2017
Tracxn Research - Healthcare Analytics Landscape, February 2017Tracxn
 
MongoDB NoSQL database a deep dive -MyWhitePaper
MongoDB  NoSQL database a deep dive -MyWhitePaperMongoDB  NoSQL database a deep dive -MyWhitePaper
MongoDB NoSQL database a deep dive -MyWhitePaperRajesh Kumar
 
Tracxn Research - Finance & Accounting Landscape, February 2017
Tracxn Research - Finance & Accounting Landscape, February 2017Tracxn Research - Finance & Accounting Landscape, February 2017
Tracxn Research - Finance & Accounting Landscape, February 2017Tracxn
 
Tracxn Research - Insurance Tech Landscape, February 2017
Tracxn Research - Insurance Tech Landscape, February 2017Tracxn Research - Insurance Tech Landscape, February 2017
Tracxn Research - Insurance Tech Landscape, February 2017Tracxn
 
Tracxn Research - Mobile Advertising Landscape, February 2017
Tracxn Research - Mobile Advertising Landscape, February 2017Tracxn Research - Mobile Advertising Landscape, February 2017
Tracxn Research - Mobile Advertising Landscape, February 2017Tracxn
 
Enabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical EnterpriseEnabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical EnterpriseHortonworks
 
Tugas4 1412510602 dewi_apriliani
Tugas4 1412510602 dewi_aprilianiTugas4 1412510602 dewi_apriliani
Tugas4 1412510602 dewi_aprilianidewiapril1996
 
Business Models 2.0 - Freemium & Platform based business models
Business Models 2.0 - Freemium & Platform based business modelsBusiness Models 2.0 - Freemium & Platform based business models
Business Models 2.0 - Freemium & Platform based business modelsMichalGromek
 
GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...
GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...
GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...Oleg Shalygin
 
Inside SQL Server In-Memory OLTP
Inside SQL Server In-Memory OLTPInside SQL Server In-Memory OLTP
Inside SQL Server In-Memory OLTPBob Ward
 
Developing streaming applications with apache apex (strata + hadoop world)
Developing streaming applications with apache apex (strata + hadoop world)Developing streaming applications with apache apex (strata + hadoop world)
Developing streaming applications with apache apex (strata + hadoop world)Apache Apex
 
Brk3288 sql server v.next with support on linux, windows and containers was...
Brk3288 sql server v.next with support on linux, windows and containers   was...Brk3288 sql server v.next with support on linux, windows and containers   was...
Brk3288 sql server v.next with support on linux, windows and containers was...Bob Ward
 
Tugas 4 0317-imelda felicia-1412510545
Tugas 4 0317-imelda felicia-1412510545Tugas 4 0317-imelda felicia-1412510545
Tugas 4 0317-imelda felicia-1412510545imeldafelicia
 
Webinar: Fighting Fraud with Graph Databases
Webinar: Fighting Fraud with Graph DatabasesWebinar: Fighting Fraud with Graph Databases
Webinar: Fighting Fraud with Graph DatabasesDataStax
 
Rootlinux17: An introduction to Xen Project Virtualisation
Rootlinux17:  An introduction to Xen Project VirtualisationRootlinux17:  An introduction to Xen Project Virtualisation
Rootlinux17: An introduction to Xen Project VirtualisationThe Linux Foundation
 
Europa AI startup scaleups report 2016
Europa AI startup scaleups report 2016 Europa AI startup scaleups report 2016
Europa AI startup scaleups report 2016 Ian Beckett
 

Destacado (20)

Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...
 
2017 iosco research report on financial technologies (fintech)
2017 iosco research report on  financial technologies (fintech)2017 iosco research report on  financial technologies (fintech)
2017 iosco research report on financial technologies (fintech)
 
2015 Internet Trends Report
2015 Internet Trends Report2015 Internet Trends Report
2015 Internet Trends Report
 
Tracxn Research - Healthcare Analytics Landscape, February 2017
Tracxn Research - Healthcare Analytics Landscape, February 2017Tracxn Research - Healthcare Analytics Landscape, February 2017
Tracxn Research - Healthcare Analytics Landscape, February 2017
 
MongoDB NoSQL database a deep dive -MyWhitePaper
MongoDB  NoSQL database a deep dive -MyWhitePaperMongoDB  NoSQL database a deep dive -MyWhitePaper
MongoDB NoSQL database a deep dive -MyWhitePaper
 
Tracxn Research - Finance & Accounting Landscape, February 2017
Tracxn Research - Finance & Accounting Landscape, February 2017Tracxn Research - Finance & Accounting Landscape, February 2017
Tracxn Research - Finance & Accounting Landscape, February 2017
 
Tracxn Research - Insurance Tech Landscape, February 2017
Tracxn Research - Insurance Tech Landscape, February 2017Tracxn Research - Insurance Tech Landscape, February 2017
Tracxn Research - Insurance Tech Landscape, February 2017
 
Tracxn Research - Mobile Advertising Landscape, February 2017
Tracxn Research - Mobile Advertising Landscape, February 2017Tracxn Research - Mobile Advertising Landscape, February 2017
Tracxn Research - Mobile Advertising Landscape, February 2017
 
Enabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical EnterpriseEnabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical Enterprise
 
Tugas4 1412510602 dewi_apriliani
Tugas4 1412510602 dewi_aprilianiTugas4 1412510602 dewi_apriliani
Tugas4 1412510602 dewi_apriliani
 
Business Models 2.0 - Freemium & Platform based business models
Business Models 2.0 - Freemium & Platform based business modelsBusiness Models 2.0 - Freemium & Platform based business models
Business Models 2.0 - Freemium & Platform based business models
 
GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...
GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...
GCP - Continuous Integration and Delivery into Kubernetes with GitHub, Travis...
 
K8S in prod
K8S in prodK8S in prod
K8S in prod
 
Inside SQL Server In-Memory OLTP
Inside SQL Server In-Memory OLTPInside SQL Server In-Memory OLTP
Inside SQL Server In-Memory OLTP
 
Developing streaming applications with apache apex (strata + hadoop world)
Developing streaming applications with apache apex (strata + hadoop world)Developing streaming applications with apache apex (strata + hadoop world)
Developing streaming applications with apache apex (strata + hadoop world)
 
Brk3288 sql server v.next with support on linux, windows and containers was...
Brk3288 sql server v.next with support on linux, windows and containers   was...Brk3288 sql server v.next with support on linux, windows and containers   was...
Brk3288 sql server v.next with support on linux, windows and containers was...
 
Tugas 4 0317-imelda felicia-1412510545
Tugas 4 0317-imelda felicia-1412510545Tugas 4 0317-imelda felicia-1412510545
Tugas 4 0317-imelda felicia-1412510545
 
Webinar: Fighting Fraud with Graph Databases
Webinar: Fighting Fraud with Graph DatabasesWebinar: Fighting Fraud with Graph Databases
Webinar: Fighting Fraud with Graph Databases
 
Rootlinux17: An introduction to Xen Project Virtualisation
Rootlinux17:  An introduction to Xen Project VirtualisationRootlinux17:  An introduction to Xen Project Virtualisation
Rootlinux17: An introduction to Xen Project Virtualisation
 
Europa AI startup scaleups report 2016
Europa AI startup scaleups report 2016 Europa AI startup scaleups report 2016
Europa AI startup scaleups report 2016
 

Similar a Gs08 modernize your data platform with sql technologies wash dc

Sql server 2019 new features
Sql server 2019 new featuresSql server 2019 new features
Sql server 2019 new featuresGeorge Walters
 
Experience sql server on l inux and docker
Experience sql server on l inux and dockerExperience sql server on l inux and docker
Experience sql server on l inux and dockerBob Ward
 
SQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT SolutionsSQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT SolutionsMichaela Murray
 
What's new in SQL Server 2016
What's new in SQL Server 2016What's new in SQL Server 2016
What's new in SQL Server 2016James Serra
 
Postgres for Digital Transformation: NoSQL Features, Replication, FDW & More
Postgres for Digital Transformation:NoSQL Features, Replication, FDW & MorePostgres for Digital Transformation:NoSQL Features, Replication, FDW & More
Postgres for Digital Transformation: NoSQL Features, Replication, FDW & MoreAshnikbiz
 
Modernization sql server 2016
Modernization   sql server 2016Modernization   sql server 2016
Modernization sql server 2016Kiki Noviandi
 
SQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux IntroductionSQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux IntroductionTravis Wright
 
Nordic infrastructure Conference 2017 - SQL Server on Linux Overview
Nordic infrastructure Conference 2017 - SQL Server on Linux OverviewNordic infrastructure Conference 2017 - SQL Server on Linux Overview
Nordic infrastructure Conference 2017 - SQL Server on Linux OverviewTravis Wright
 
SQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT SolutionsSQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT SolutionsMichaela Murray
 
Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)
Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)
Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)Bob Ward
 
Microsoft Data Platform - What's included
Microsoft Data Platform - What's includedMicrosoft Data Platform - What's included
Microsoft Data Platform - What's includedJames Serra
 
In-memory ColumnStore Index
In-memory ColumnStore IndexIn-memory ColumnStore Index
In-memory ColumnStore IndexSolidQ
 
SQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux IntroductionSQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux IntroductionTravis Wright
 
Sql Server 2016_datasheet
Sql Server 2016_datasheetSql Server 2016_datasheet
Sql Server 2016_datasheetMILL5
 
SQL_Server_2016_datasheet
SQL_Server_2016_datasheetSQL_Server_2016_datasheet
SQL_Server_2016_datasheetrohitpoudel
 
Prague data management meetup 2018-03-27
Prague data management meetup 2018-03-27Prague data management meetup 2018-03-27
Prague data management meetup 2018-03-27Martin Bém
 
44spotkaniePLSSUGWRO_CoNowegowKrainieChmur
44spotkaniePLSSUGWRO_CoNowegowKrainieChmur44spotkaniePLSSUGWRO_CoNowegowKrainieChmur
44spotkaniePLSSUGWRO_CoNowegowKrainieChmurTobias Koprowski
 
Discovery Day 2019 Sofia - What is new in SQL Server 2019
Discovery Day 2019 Sofia - What is new in SQL Server 2019Discovery Day 2019 Sofia - What is new in SQL Server 2019
Discovery Day 2019 Sofia - What is new in SQL Server 2019Ivan Donev
 
SQL Server 2017 Overview and Partner Opportunities
SQL Server 2017 Overview and Partner OpportunitiesSQL Server 2017 Overview and Partner Opportunities
SQL Server 2017 Overview and Partner OpportunitiesTravis Wright
 

Similar a Gs08 modernize your data platform with sql technologies wash dc (20)

Sql server 2019 new features
Sql server 2019 new featuresSql server 2019 new features
Sql server 2019 new features
 
Experience sql server on l inux and docker
Experience sql server on l inux and dockerExperience sql server on l inux and docker
Experience sql server on l inux and docker
 
SQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT SolutionsSQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT Solutions
 
What's new in SQL Server 2016
What's new in SQL Server 2016What's new in SQL Server 2016
What's new in SQL Server 2016
 
Postgres for Digital Transformation: NoSQL Features, Replication, FDW & More
Postgres for Digital Transformation:NoSQL Features, Replication, FDW & MorePostgres for Digital Transformation:NoSQL Features, Replication, FDW & More
Postgres for Digital Transformation: NoSQL Features, Replication, FDW & More
 
Modernization sql server 2016
Modernization   sql server 2016Modernization   sql server 2016
Modernization sql server 2016
 
SQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux IntroductionSQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux Introduction
 
Nordic infrastructure Conference 2017 - SQL Server on Linux Overview
Nordic infrastructure Conference 2017 - SQL Server on Linux OverviewNordic infrastructure Conference 2017 - SQL Server on Linux Overview
Nordic infrastructure Conference 2017 - SQL Server on Linux Overview
 
SQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT SolutionsSQL Server 2019 hotlap - WARDY IT Solutions
SQL Server 2019 hotlap - WARDY IT Solutions
 
Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)
Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)
Brk2045 upgrade sql server 2017 (on prem, iaa-s and paas)
 
Microsoft Data Platform - What's included
Microsoft Data Platform - What's includedMicrosoft Data Platform - What's included
Microsoft Data Platform - What's included
 
In-memory ColumnStore Index
In-memory ColumnStore IndexIn-memory ColumnStore Index
In-memory ColumnStore Index
 
SQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux IntroductionSQL Server 2017 on Linux Introduction
SQL Server 2017 on Linux Introduction
 
Sql Server 2016_datasheet
Sql Server 2016_datasheetSql Server 2016_datasheet
Sql Server 2016_datasheet
 
Sql server 2016 datasheet
Sql server 2016 datasheetSql server 2016 datasheet
Sql server 2016 datasheet
 
SQL_Server_2016_datasheet
SQL_Server_2016_datasheetSQL_Server_2016_datasheet
SQL_Server_2016_datasheet
 
Prague data management meetup 2018-03-27
Prague data management meetup 2018-03-27Prague data management meetup 2018-03-27
Prague data management meetup 2018-03-27
 
44spotkaniePLSSUGWRO_CoNowegowKrainieChmur
44spotkaniePLSSUGWRO_CoNowegowKrainieChmur44spotkaniePLSSUGWRO_CoNowegowKrainieChmur
44spotkaniePLSSUGWRO_CoNowegowKrainieChmur
 
Discovery Day 2019 Sofia - What is new in SQL Server 2019
Discovery Day 2019 Sofia - What is new in SQL Server 2019Discovery Day 2019 Sofia - What is new in SQL Server 2019
Discovery Day 2019 Sofia - What is new in SQL Server 2019
 
SQL Server 2017 Overview and Partner Opportunities
SQL Server 2017 Overview and Partner OpportunitiesSQL Server 2017 Overview and Partner Opportunities
SQL Server 2017 Overview and Partner Opportunities
 

Más de Bob Ward

Build new age applications on azures intelligent data platform
Build new age applications on azures intelligent data platformBuild new age applications on azures intelligent data platform
Build new age applications on azures intelligent data platformBob Ward
 
Brk2051 sql server on linux and docker
Brk2051 sql server on linux and dockerBrk2051 sql server on linux and docker
Brk2051 sql server on linux and dockerBob Ward
 
Experience SQL Server 2017: The Modern Data Platform
Experience SQL Server 2017: The Modern Data PlatformExperience SQL Server 2017: The Modern Data Platform
Experience SQL Server 2017: The Modern Data PlatformBob Ward
 
Inside sql server in memory oltp sql sat nyc 2017
Inside sql server in memory oltp sql sat nyc 2017Inside sql server in memory oltp sql sat nyc 2017
Inside sql server in memory oltp sql sat nyc 2017Bob Ward
 
Keep your environment always on with sql server 2016 sql bits 2017
Keep your environment always on with sql server 2016 sql bits 2017Keep your environment always on with sql server 2016 sql bits 2017
Keep your environment always on with sql server 2016 sql bits 2017Bob Ward
 
Sql server 2016 it just runs faster sql bits 2017 edition
Sql server 2016 it just runs faster   sql bits 2017 editionSql server 2016 it just runs faster   sql bits 2017 edition
Sql server 2016 it just runs faster sql bits 2017 editionBob Ward
 
SQL Server In-Memory OLTP: What Every SQL Professional Should Know
SQL Server In-Memory OLTP: What Every SQL Professional Should KnowSQL Server In-Memory OLTP: What Every SQL Professional Should Know
SQL Server In-Memory OLTP: What Every SQL Professional Should KnowBob Ward
 

Más de Bob Ward (7)

Build new age applications on azures intelligent data platform
Build new age applications on azures intelligent data platformBuild new age applications on azures intelligent data platform
Build new age applications on azures intelligent data platform
 
Brk2051 sql server on linux and docker
Brk2051 sql server on linux and dockerBrk2051 sql server on linux and docker
Brk2051 sql server on linux and docker
 
Experience SQL Server 2017: The Modern Data Platform
Experience SQL Server 2017: The Modern Data PlatformExperience SQL Server 2017: The Modern Data Platform
Experience SQL Server 2017: The Modern Data Platform
 
Inside sql server in memory oltp sql sat nyc 2017
Inside sql server in memory oltp sql sat nyc 2017Inside sql server in memory oltp sql sat nyc 2017
Inside sql server in memory oltp sql sat nyc 2017
 
Keep your environment always on with sql server 2016 sql bits 2017
Keep your environment always on with sql server 2016 sql bits 2017Keep your environment always on with sql server 2016 sql bits 2017
Keep your environment always on with sql server 2016 sql bits 2017
 
Sql server 2016 it just runs faster sql bits 2017 edition
Sql server 2016 it just runs faster   sql bits 2017 editionSql server 2016 it just runs faster   sql bits 2017 edition
Sql server 2016 it just runs faster sql bits 2017 edition
 
SQL Server In-Memory OLTP: What Every SQL Professional Should Know
SQL Server In-Memory OLTP: What Every SQL Professional Should KnowSQL Server In-Memory OLTP: What Every SQL Professional Should Know
SQL Server In-Memory OLTP: What Every SQL Professional Should Know
 

Último

If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...
If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...
If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...Maxim Salnikov
 
Enterprise Content Managements Solutions
Enterprise Content Managements SolutionsEnterprise Content Managements Solutions
Enterprise Content Managements SolutionsIQBG inc
 
Steps to Successfully Hire Ionic Developers
Steps to Successfully Hire Ionic DevelopersSteps to Successfully Hire Ionic Developers
Steps to Successfully Hire Ionic Developersmichealwillson701
 
Mobile App Development process | Expert Tips
Mobile App Development process | Expert TipsMobile App Development process | Expert Tips
Mobile App Development process | Expert Tipsmichealwillson701
 
Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...
Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...
Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...telebusocialmarketin
 
Unlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insightsUnlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insightsconfluent
 
BusinessGPT - SECURITY AND GOVERNANCE FOR GENERATIVE AI.pptx
BusinessGPT  - SECURITY AND GOVERNANCE  FOR GENERATIVE AI.pptxBusinessGPT  - SECURITY AND GOVERNANCE  FOR GENERATIVE AI.pptx
BusinessGPT - SECURITY AND GOVERNANCE FOR GENERATIVE AI.pptxAGATSoftware
 
03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...
03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...
03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...jackiepotts6
 
Boost Efficiency: Sabre API Integration Made Easy
Boost Efficiency: Sabre API Integration Made EasyBoost Efficiency: Sabre API Integration Made Easy
Boost Efficiency: Sabre API Integration Made Easymichealwillson701
 
VuNet software organisation powerpoint deck
VuNet software organisation powerpoint deckVuNet software organisation powerpoint deck
VuNet software organisation powerpoint deckNaval Singh
 
Einstein Copilot Conversational AI for your CRM.pdf
Einstein Copilot Conversational AI for your CRM.pdfEinstein Copilot Conversational AI for your CRM.pdf
Einstein Copilot Conversational AI for your CRM.pdfCloudMetic
 
MUT4SLX: Extensions for Mutation Testing of Stateflow Models
MUT4SLX: Extensions for Mutation Testing of Stateflow ModelsMUT4SLX: Extensions for Mutation Testing of Stateflow Models
MUT4SLX: Extensions for Mutation Testing of Stateflow ModelsUniversity of Antwerp
 
Large Scale Architecture -- The Unreasonable Effectiveness of Simplicity
Large Scale Architecture -- The Unreasonable Effectiveness of SimplicityLarge Scale Architecture -- The Unreasonable Effectiveness of Simplicity
Large Scale Architecture -- The Unreasonable Effectiveness of SimplicityRandy Shoup
 
openEuler Community Overview - a presentation showing the current scale
openEuler Community Overview - a presentation showing the current scaleopenEuler Community Overview - a presentation showing the current scale
openEuler Community Overview - a presentation showing the current scaleShane Coughlan
 
BATbern52 Swisscom's Journey into Data Mesh
BATbern52 Swisscom's Journey into Data MeshBATbern52 Swisscom's Journey into Data Mesh
BATbern52 Swisscom's Journey into Data MeshBATbern
 
Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...
Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...
Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...MyFAA
 
Revolutionize Your Field Service Management with FSM Grid
Revolutionize Your Field Service Management with FSM GridRevolutionize Your Field Service Management with FSM Grid
Revolutionize Your Field Service Management with FSM GridMathew Thomas
 
8 Steps to Build a LangChain RAG Chatbot.
8 Steps to Build a LangChain RAG Chatbot.8 Steps to Build a LangChain RAG Chatbot.
8 Steps to Build a LangChain RAG Chatbot.Ritesh Kanjee
 
Flutter the Future of Mobile App Development - 5 Crucial Reasons.pdf
Flutter the Future of Mobile App Development - 5 Crucial Reasons.pdfFlutter the Future of Mobile App Development - 5 Crucial Reasons.pdf
Flutter the Future of Mobile App Development - 5 Crucial Reasons.pdfMind IT Systems
 

Último (20)

If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...
If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...
If your code could speak, what would it tell you? Let GitHub Copilot Chat hel...
 
Enterprise Content Managements Solutions
Enterprise Content Managements SolutionsEnterprise Content Managements Solutions
Enterprise Content Managements Solutions
 
Steps to Successfully Hire Ionic Developers
Steps to Successfully Hire Ionic DevelopersSteps to Successfully Hire Ionic Developers
Steps to Successfully Hire Ionic Developers
 
Mobile App Development process | Expert Tips
Mobile App Development process | Expert TipsMobile App Development process | Expert Tips
Mobile App Development process | Expert Tips
 
20140812 - OBD2 Solution
20140812 - OBD2 Solution20140812 - OBD2 Solution
20140812 - OBD2 Solution
 
Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...
Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...
Telebu Social -Whatsapp Business API : Mastering Omnichannel Business Communi...
 
Unlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insightsUnlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insights
 
BusinessGPT - SECURITY AND GOVERNANCE FOR GENERATIVE AI.pptx
BusinessGPT  - SECURITY AND GOVERNANCE  FOR GENERATIVE AI.pptxBusinessGPT  - SECURITY AND GOVERNANCE  FOR GENERATIVE AI.pptx
BusinessGPT - SECURITY AND GOVERNANCE FOR GENERATIVE AI.pptx
 
03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...
03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...
03.2024_North America VMUG Optimizing RevOps using the power of ChatGPT in Ma...
 
Boost Efficiency: Sabre API Integration Made Easy
Boost Efficiency: Sabre API Integration Made EasyBoost Efficiency: Sabre API Integration Made Easy
Boost Efficiency: Sabre API Integration Made Easy
 
VuNet software organisation powerpoint deck
VuNet software organisation powerpoint deckVuNet software organisation powerpoint deck
VuNet software organisation powerpoint deck
 
Einstein Copilot Conversational AI for your CRM.pdf
Einstein Copilot Conversational AI for your CRM.pdfEinstein Copilot Conversational AI for your CRM.pdf
Einstein Copilot Conversational AI for your CRM.pdf
 
MUT4SLX: Extensions for Mutation Testing of Stateflow Models
MUT4SLX: Extensions for Mutation Testing of Stateflow ModelsMUT4SLX: Extensions for Mutation Testing of Stateflow Models
MUT4SLX: Extensions for Mutation Testing of Stateflow Models
 
Large Scale Architecture -- The Unreasonable Effectiveness of Simplicity
Large Scale Architecture -- The Unreasonable Effectiveness of SimplicityLarge Scale Architecture -- The Unreasonable Effectiveness of Simplicity
Large Scale Architecture -- The Unreasonable Effectiveness of Simplicity
 
openEuler Community Overview - a presentation showing the current scale
openEuler Community Overview - a presentation showing the current scaleopenEuler Community Overview - a presentation showing the current scale
openEuler Community Overview - a presentation showing the current scale
 
BATbern52 Swisscom's Journey into Data Mesh
BATbern52 Swisscom's Journey into Data MeshBATbern52 Swisscom's Journey into Data Mesh
BATbern52 Swisscom's Journey into Data Mesh
 
Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...
Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...
Take Advantage of Mx Tracking Flight Scheduling Solutions to Streamline Your ...
 
Revolutionize Your Field Service Management with FSM Grid
Revolutionize Your Field Service Management with FSM GridRevolutionize Your Field Service Management with FSM Grid
Revolutionize Your Field Service Management with FSM Grid
 
8 Steps to Build a LangChain RAG Chatbot.
8 Steps to Build a LangChain RAG Chatbot.8 Steps to Build a LangChain RAG Chatbot.
8 Steps to Build a LangChain RAG Chatbot.
 
Flutter the Future of Mobile App Development - 5 Crucial Reasons.pdf
Flutter the Future of Mobile App Development - 5 Crucial Reasons.pdfFlutter the Future of Mobile App Development - 5 Crucial Reasons.pdf
Flutter the Future of Mobile App Development - 5 Crucial Reasons.pdf
 

Gs08 modernize your data platform with sql technologies wash dc

  • 3. • Disparate systems and processes • Multiple tools and skillsets • High cost of ownership • Siloed insights on disconnected data • Costly data movement and delay Challenges of the Modern Data Platform Fragmented architectures are inefficient AnalyticsVisualization Relational in the cloud Analytics Visualization Hadoop { } NoSQL Data Lake AnalyticsVisualization Relational DBAppliance Analytics Visualization Hadoop Appliance CloudOn-premises Relational Non-relational
  • 4. Azure SQL Database Azure SQL Data Warehouse SQL Server 2016 on VM Analytics Platform System Azure Data Lake SQL Server 2016 Analytics Platform System SQL Relational Non-relational On-premisesCloudMicrosoft Data Platform Transforming data into intelligent action • Manage all your data in a mission critical, scalable, secure way • Gain deep insights across all of your data without data movement • Utilize existing skills and investments • Consistent on-premises, cloud and hybrid experiences Federated query Business intelligence Machine learning & advanced analytics Insights
  • 7. Continuous Innovation End-to-end mobile BI Advanced Analytics Enterprise-grade DW Mission critical OLTP The best SQL Server release in history SQL Server 2016 Speed Agility Proven Feedback SQL DB SQL DB SQL DB SQL DB New innovations Across customer base Cloud-First Approach + DevOps Continuous enhancements Hybridcloud
  • 8. National Institute of Standards and Technology Comprehensive Vulnerability Database update 12/2016. Everything built-inTPC-H Oracle is #5#2 SQL Server #1 SQL Server #3 SQL Server The Power of SQL Server Everything built-in June 2016 SQL Server 2016 TPC-E 0 1 4 0 0 3 0 34 29 22 15 5 22 16 6 43 20 69 18 49 74 3 0 10 20 30 40 50 60 70 80 2010 2011 2012 2013 2014 2015 2016 SQL Server Oracle MySQL2 SAP HANA 1/12
  • 9. Only data solution to encrypt your data at rest and in motion Connect your relational data to big data with PolyBase Real-time operational analytics without impacting performance Up to 30x faster transactions, 100x faster queries with InMemory Unparalleled choice for developer tools and languages 1 T-SQL Java C/C++ C#/VB.NET PHP Node.js Python Ruby For all your applications Innovations across all editions Available now SQL Server 2016 SP1
  • 10. On the platform of your choice SQL Server v.Next Targeting CY2017 SQL Server v.Next GA* SQL Server v.Next Public Preview available now on Linux, Windows, and Docker.
  • 11. Just Runs Faster Core Engine Scalability Automatic Soft NUMA Dynamic Memory Objects SOS_RWLock Fair and Balanced Scheduling Parallel INSERT..SELECT Parallel Redo DBCC DBCC Scalability DBCC Extended Checks TempDB Goodbye Trace Flags Setup and Automatic Configuration of Files Optimistic Latching I/O Instant File Initialization is No Longer Hidden Multiple Log Writers Indirect Checkpoint Default Just Makes Sense Log I/O at the Speed of Memory Spatial Native Implementations TVP and Index Improvements Columnstore Batch Mode and Window Functions Always On Availability Groups Turbocharged Better Compression and Encryption
  • 12. Persisted Log Buffer The evolution of storage HDD  SSD (ms) PCI NVMe SSD (μs) Tired of WRITELOG waits? Along comes NVDIMM(ns) Windows Server 2016 supports block storage (standard I/O path) A new interface for DirectAccess (DAX) Persistent Memory (PM) Watch these videos Channel 9 on SQL and PMM NVDIMM on Win 2016 from build Format your NTFS volume with /dax on Windows Server 2016 Create a 2nd tlog file on this new volume on SQL Server 2016 SP1 Tail of the log is now a “memcpy” so commit is fast WRITELOG waits = 0 ms here
  • 13. Mission critical platform Deeper Insights Hyperscale In-Memory OLTP Greater T-SQL surface area, terabytes of memory supported, and higher number of parallel CPUs Query Store A flight data recorder for your database Always Encrypted Sensitive data remains encrypted at all times, with ability to query Row-Level Security Fine-grained access control for table rows Enhanced Always On Distributed Availability Groups, Basic Availability Groups, Automatic Failover The richest set of diagnostics in the industry. Read more here
  • 14. High-Performance Execution Engines ColumnStore + Batch Mode Execution • Columnar compression to save space in memory and on disk • New execution engine that optimizes instructions/row and minimizes CPU data bus I/O stalls • Often gives speedups of 10x • Allows you to store, manage, and gain value out of significantly more data In-Memory OLTP Engine Model • Lock-free algorithms • Optimistic concurrency model • Full transactional support • Compiled procedures • Can give significant speedups (2x- 50x) on high-end OLTP applications Capturing technical breakthroughs in two areas These enable you to write SQL and leverage ever- increasing performance for your applications MissionCriticalPlatform
  • 16. Secure Code • Secure development lifecycle • Least vulnerable last 6 years Most Secure Database Secure engine Least vulnerable last 6 years 0 2 11 8 0 1 4 0 0 3 69 53 53 55 34 29 22 15 5 22 5 28 25 29 21 6 13 3 0 6 16 16 9 8 6 43 20 69 18 49 3 0 10 20 30 40 50 60 70 80 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 SQL Server Oracle DB2 MySQL SAP HANA * National Institute of Standards and Technology Comprehensive Vulnerability Database update 10/2015 while being most utilized MissionCriticalPlatform
  • 17. Most Secure Database Surrounded by layers of protection Secure Code • Secure development lifecycle • Least vulnerable last 6 years • SQL Threat Detection • SQL Server Auditing • Row-level Security • Dynamic Data Masking • Always Encrypted • Transparent Data Encryption • Encryption-in-flight Control Access • SQL Authentication • Windows Authentication • Azure Active Directory Auth. Monitor activity Control access Protect data Come to the instructor lead security lab at 4:45 pm today! MissionCriticalPlatform
  • 18. trust boundary "SELECT Name FROM Customers WHERE SSN = @SSN","111-22-3333" Always Encrypted Protect data at rest and in motion, on-premises and in the cloud Name Wayne Jefferson ADO .NET Name 0x19ca706fbd9a Result SetResult Set Client Name SSN Country 0x19ca706fbd9a 0x7ff654ae6d USA SQL Server or SQL Database "SELECT Name FROM Customers WHERE SSN = @SSN",0x7ff654ae6d ciphertext Encrypted sensitive data and corresponding keys are never seen in plaintext in SQL Server dbo.Customers ciphertext Security MissionCriticalPlatform
  • 19. Optimizing query performance and costs Query Store = flight data recorder for databases Built-in query monitoring • Negligible perf & storage overhead • Survives failover, memory pressure, … • Data ready when that incident happens T-SQL interface and SSMS UX Top insights into your workload • Query and resource stats • Query plans Developer App User Azure application On-premise Developer needs to find and fix the underlying problem, ASAP Customer reports the issue (app is slow/unresponsive) MissionCriticalPlatform
  • 21. Improved Always On Availability Groups • 3 Replicas for Automatic Failover • Database Failure Detection Higher Availability • Support for Column-store Indexes • Load Balancing of Read Workloads More Powerful Readable Secondaries • 4X Synchronization ThroughputScalability • Different Windows Clusters • Different Windows Domains Flexibility • Basic Availability Groups in Standard Edition Licensing Always On Turbocharged MissionCriticalPlatform
  • 22. Mission critical platform Deeper Insights Hyperscale Real-time operational analytics Running of analytical workloads concurrently with OLTP workloads R Integration Insights from data across SQL Server and Hadoop with the simplicity of T-SQL PolyBase Insights from data across SQL Server and Hadoop with the simplicity of T-SQL Mobile BI Mobile reports on SSRS with Mobile Report Publisher Temporal Tables, JSON Track change history, integrate with modern service easily
  • 23. 0100101010110 SQL Server OLTP SQL Server data warehouse ETL In-memory ColumnStore In-memory OLTP Real-time fraud detection Operational analytics Single system for OLTP and real-time analytics Fraud detected 2-24 hrs DeeperInsights
  • 24. Data Scientist Interact directly with data Built-in to SQL Server Data Developer/DBA Manage data and analytics together Built-in advanced analytics Running R algorithms at massive data scale Example Solutions • Salesforecasting • Warehouse efficiency • Predictive maintenance Relational Data Analytic Library T-SQL Interface Extensibility ? R RIntegration 010010 100100 010101 Microsoft Azure Marketplace New R scripts 010010 100100 010101 010010 100100 010101 010010 100100 010101 010010 100100 010101 010010 100100 010101 • Credit risk protection DeeperInsights
  • 25. PolyBase Query relational and non-relational data with T-SQL T-SQL query SQL Server Hadoop Quote: ************************ ********************** ********************* ********************** *********************** $658.39 Jim Gray Name 11/13/58 DOB WA State Ann Smith 04/29/76 ME DeeperInsights
  • 26. Support for Temporal Data Track historical data DeeperInsights • Data changes over time (!) • Databases naturally provide a current view • But an historical perspective is often critical Time travel Data audit Predictive analytics Repair record-level corruptions
  • 28. Mission critical platform Deeper Insights Hyperscale Stretch Database Stretch operational tables in a secure manner into Azure for cost-effective historic data availability. Enhanced backup to Azure Faster restore times, 50% reduction in storage. Larger DBs
  • 29. Order history Name SSN Date Jane Doe cm61ba906fd 2/28/2005 Jim Gray ox7ff654ae6d 3/18/2005 John Smith i2y36cg776rg 4/10/2005 Bill Brown nx290pldo90l 4/27/2005 Sue Daniels ypo85ba616rj 5/12/2005 Sarah Jones bns51ra806fd 5/22/2005 Jake Marks mci12hh906fj 6/07/2005 Order history Name SSN Date Jane Doe cm61ba906fd 2/28/2005 Jim Gray ox7ff654ae6d 3/18/2005 John Smith i2y36cg776rg 4/10/2005 Bill Brown nx290pldo90l 4/27/2005 Customer data Product data Order History Stretch to cloud Stretch SQL Server into Azure Stretch cold data to Azure with remote query processing App Query Microsoft Azure  Jim Gray ox7ff654ae6d 3/18/2005 HyperscaleCloud
  • 31. Fully managed Database Service … So you can focus on your Business • Built for SaaS and Enterprise applications • Predictable performance & Pricing • Elastic database pool for unpredictable SaaS workloads • 99.99% availability built-in • Geo-replication and restore services for data protection • Secure and compliant for your sensitive data • Fully compatible with SQL Server 2016 databases
  • 32. Predictable workloads Single databases or partitioned data across multiple databases; scale between service tiers and performance levels as capacity needs fluctuate. Scaledatabases upasneeded Scale out/in the pool … Single database or partitioned databases Customer 1 Customer 2 Customer 3 Customer #N… Unpredictable workloads For large numbers of databases with unpredictable performance demands; pool resources to be shared between these databases. Elastic Database Pool Databasesconsume resourcesasneeded Managing large numbers of Databases
  • 33. SQL Database Service Tiers (single DB model) *The 99.99% availability SLA does not apply to the existing Web and Business editions, which will continue to be supported at 99.9% availability. Built For Available SLA Database Max Size Business Continuity Security Performance Objectives Database Transaction Units (DTUs) Available Tiers ($/Month) and GA Price Point-in-time Restore (“oops” Recovery) BASIC PREMIUMSTANDARD P1S0 Light transactional workloads Medium transactional workloads Heavy Transactional Workloads 99.99%* 2 GB 250 GB 500 – 1,000 GB (more soon) Any point within 7 days Any point within 14 days Any point within 35 days Geo-restore Geo-replication, standby secondary Active geo-replication, up to four readable secondary backups Auditing, row-level security, dynamic data masking, encryption Transactions per hour Transactions per minute Transactions per second 5 $4.99 S1 S2 S3 P2 P4 P6 P11 10 20 50 100 $15 $30 $75 $150 125 250 500 1,000 1,750 $465 $930 $1,860 $3,720 $7,001 P15 … 4,000 $16,003
  • 34. Azure SQL Data Warehouse • A relational data-warehouse-as-a-service, fully managed by Microsoft. • Industries first elastic cloud data warehouse with proven SQL Server capabilities. • Support your smallest to your largest data storage needs. Saas Azure Public Cloud Office 365Office 365 AzureAzure
  • 36. Source Target Windows Azure Windows Azure Tool(s) DMA DMA SSMA Legacy Modern Comparison Reports A’ SQL 2008 Instance Extensive tracing Statistical Analysis Analyze Results B SQL 2016 Instance Extensive tracing capture prod workload
  • 37. Migrations by Industry Financial Services 139 Discrete Manufacturing 122 Retail & Consumer Goods 113 Government 105 Health 94 Professional Services 93 Process Manufacturing & Resources 59 Hospitality & Travel 44 Telecommunications 36 Power & Utilities 31 Other Industries 119 TOTAL 955
  • 38. Azure SQL Database Azure SQL Data Warehouse SQL Server 2016 on VM Analytics Platform System Azure Data Lake SQL Server 2016 Analytics Platform System SQL Relational Non-relational On-premisesCloudMicrosoft Data Platform Transforming data into intelligent action • Manage all your data in a mission critical, scalable, secure way • Gain deep insights across all of your data without data movement • Utilize existing skills and investments • Consistent on-premises, cloud and hybrid experiences Federated query Business intelligence Machine learning & advanced analytics Insights
  • 43. In-Memory Transactional Processing SQL Server Integration • Same manageability, administration & development experience • Integrated queries & transactions • Integrated HA and backup/restore In-Memory Data Access • Indexes (hash and range) exist only in memory • Records exist only in memory (pointers from indexes) • No buffer pool, B-trees • Stream-based storage T-SQL Compiled to Machine Code • T-SQL compiled to machine code via C code generator • Invoking a procedure is just a DLL entry-point • Aggressive optimizations @ compile-time Declining memory price Many-core processorsStalling CPU clock rate Lower TCO Hardware trends Business Integrated experience High performance data operations Efficient business-logic processing Customer Benefits ArchitecturalPillarsDrivers High Concurrency • Core engine uses lock-free algorithms • No lock manager, latches or spinlocks • Multi-version optimistic concurrency control with full ACID support Frictionless scale-up
  • 44. 45 Column-Store Indexes Improved compression: Data from same domain compress better Reduced I/O: Fetch only columns needed … Row-store indexes Column-store indexes Ideal for OLTP Efficient operation on small set of rows C5C1 C2 C3 C4 Improved Performance: More data fits in memory Optimized for CPU utilization Ideal for DW Workload
  • 48. • Interchange data with apps and services • Exploit agility of NoSQL to easily extend your app SQL Server Web app, service
  • 49. CREATE TABLE Departments ( DeptId int NOT NULL PRIMARY KEY CLUSTERED , DeptName varchar(50) NOT NULL , ManagerId int NULL ) ; How Temporal Tables Work End-to-endmobileBI
  • 50. CREATE TABLE Departments ( DeptId int NOT NULL PRIMARY KEY CLUSTERED , DeptName varchar(50) NOT NULL , ManagerId int NULL , SysStartTime datetime2 GENERATED ALWAYS AS ROW START NOT NULL , SysEndTime datetime2 GENERATED ALWAYS AS ROW END NOT NULL , PERIOD FOR SYSTEM_TIME (SysStartTime, SysEndTime) ) WITH (SYSTEM_VERSIONING = ON (HISTORY_TABLE = DepartmentHistory)) ; How Temporal Tables Work End-to-endmobileBI
  • 51. How Temporal Tables Work Insert prior version Start EndDeptId DeptName ManagerId DepartmentsHistory End-to-endmobileBI Update / Delete Departments (temporal) Departments Start EndDeptId DeptName ManagerId
  • 52. How Temporal Tables Work Start EndDeptId DeptName ManagerId DepartmentsHistory End-to-endmobileBI Normal query SELECT * FROM Departments GO Departments (temporal) Departments Start EndDeptId DeptName ManagerId
  • 53. How Temporal Tables Work Start EndDeptId DeptName ManagerId Departments DepartmentsHistory End-to-endmobileBI Temporal query SELECT * FROM Departments FOR SYSTEM_TIME AS OF '2015.01.01' GO Departments (temporal) Start EndDeptId DeptName ManagerId
  • 54. Paginated reports Design beautiful documents using updated tools and new features Mobile reports Create responsive, interactive reports optimized for mobile devices Modern web portal Consume both types of reports in one web portal using modern browsers SQL Server Reporting Services
  • 55. SQL Server Analysis Services 2016 Easily create models IT pro Increase adoption Business analyst Share insights faster Faster time to insight BI consumers
  • 57. OLTP Industry leading TCO $648K + $120 per user for Power BI SQL Server 2016 ADVANCED ANALYTICS BUSINESS INTELLIGENCE OLTP DATA WAREHOUSING 3.4x 20x per user $2.2M + $2,230 per user for BI Note: For OLTP and DW scenario, the price comparison is based on a server with 2 proc, 8 cores each Built-in with SQL Server vs. expensive add-ons with Oracle Complete mobile BI In-memory End-to-end security Advanced Analytics built-in built-in built-in built-in DATA WAREHOUSING BUSINESS INTELLIGENCE ADVANCED ANALYTICS
  • 58. Easy with SQL Server migration assistants SSMA for Oracle SSMA for Sybase SSMA for DB2 SSMA for MySQL SSMA for Access

Notas del editor

  1. SQL Server is the new industry leader and SQL Server 2016 is packed with value for customers and as with our history, that value is built-in to a single enterprise sku with no additional add-ons. Let’s take a look at the top 5 reasons why you want to bet your business needs on SQL Server. If you are on SQL Server 2005 there is no better time to modernize your apps. If you are on Oracle or IBM, no better time to look again at the value you can gain today at a much lower TCO. <click> Industry leader in mission critical OLTP In case you missed, there is a new leader in Gartner’s core database MQ, where SQL Server for the first time has de-throned Oracle in both execution and vision! Microsoft SQL Server has been the industry leader for two years in a row! Customers are realizing the value that Microsoft is delivering at a rapid pace and in a customer friendly way by building-in innovation verses requiring add-ons. SQL Server also has #1 rankings across a number of TPC-E and TPC-H performance benchmarks Speaking of security and performance, let’s take a look at how we fair against the competition.<click> Most secure database SQL Server continues to be the least vulnerable database 6 years in a row. NIST (National Institute of Standards and Technology) tracks database vulnerabilities and shows SQL as the lowest even though we have more units deployed in production than both Oracle and IBM combined. So what does that mean, if you look at the chart you will see Oracle has many more vulnerabilities, this doesn’t mean that Oracle didn’t address them, but until the vulnerability patch is released and you implement it your data is at risk. Fewer vulnerabilities means fewer patches and your data is less exposed to attack. In addition, SQL Server 2016 delivers layers of protection with capabilities that can protect your data at rest and in motion, even in the memory buffer pool, without impacting database performance, along with the ability to control access and monitor threats. This multi-layered approach combined with proven track record of being least vulnerable provide you with the most secure database on the planet. <click> Highest performing data warehouse From a performance perspective, looking at TPC-H a standard benchmark particularly for Data Warehousing workloads, SQL holds the number #1, #2, and #3 spots for non-clustered scale up performance on multiple hardware platforms including HP, Lenovo and Cisco and for multiple data sizes including 1TB, 3TB and 10TB.  Oracle comes in at #4.  This not only showcases SQL Server performance, but performance at scale for data warehousing. SQL Server 2016 can scale from data marts to the biggest DW workloads.  With SQL Server 2016 enterprise you also get the rights to deploy our scale out MPP (massive parallel processing) data warehousing appliance, so again incredible value out of a single sku. <click> End to end mobile BI on any device Now let’s take a look at end to end mobile BI solution. Many of you may have heard about the Datazen acquisition we made to provide our customer with mobile BI on any device. Well in SQL Server 2016 this will be integrated into Reporting Services, which we are enhancing in a big way. What this means is you can now publish modern reports using PowerBI or Excel 2016 to an iPhone, Android phone, as well as Windows phone. Best of all its built-in so no need to buy a separate product. With the new integration of Power BI and SQL Server you can enable self-service BI in addition to mobility. Even if you choose to enable self-service BI you are doing it at a fraction of the cost of Tableau and Oracle. Even though Tableau has added mobile it’s only iOS and not Android, which is important outside of the US and Tableau is only a point solution for BI, where as SQL Server can tackle all data workloads give you BI and Advanced Analytics built-in. <click> In-database Advanced Analytics Many customers are exploring going beyond BI into predicative analytics where they want to proactively pave their businesses future with data rather than react to data. With SQL Server 2016 you can now accomplish this with built-in in-database advanced analytics. Again the key here is in-database, because when you talk to customers trying to implement advanced analytics the number one challenge is moving the data out of your database to do perform open source R models. In addition, customers want to perform analysis using R models on the latest data which you can do quickly by combining R with SQL Server in-memory technology. With 2016 you can perform R models directly in the database. In addition, customer want to run their R models on the latest data and you can do this quickly with SQL Server 2016 by combining the power of open source R with SQL Server in-memory technology for incredibly fast reads and writes. <click> In-memory across workloads In addition to these top 5 reasons, our optimized in-memory technology is fueling performance across all workloads from our in-memory OLTP that provides up to 30x transactional performance to our in-memory columnstore that give over 100x faster queries for data warehouse and BI workloads. Now with SQL Server 2016, you also have the ability to combine in-memory technologies to give you super-fast reads on top of super-fast writes to enable real-time operational analytics.<click> Consistent Experience from on-premises to cloud In addition to in-memory across all of these workloads, we can also deliver these capabilities with a consistent experience both on-premises and cloud with common development and management tools and common T-SQL. Our goal is to provide you a great experience with data no matter where you choose to implement it! <click to next slide>
  2. With SQL Server 2016 Service Pack 1, innovative features are now available across editions, so companies can scale across editions with a consistent programming surface area.
  3. With SQL Server v.Next, now in public preview, and generally available to purchase targeting mid-calendar year 2017, the power of SQL Server is available on the platform of your choice.
  4. Follow instructions in inmem_oltp\readme.txt directory
  5. 1 min
  6. TODO: Add in resources
  7. MSFT delivers the leading total cost of ownership (TCO) for Tier 1 workloads. Slide shows a comparison with Oracle. Key point - we are building things in while Oracle is adding things on. Oracle ULA (unlimited license agreement) is based on enterprise SKU but it doesn’t include in-memory, advanced analytics. Add-ons can grow to as much as $10K per core Also consider TCO over time – what future products will be packaged as add-ons from Oracle vs built-in from Microsoft? Better bet with MSFT. <click>