SlideShare a Scribd company logo
1 of 35
Download to read offline
1Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
2017 DB Trends for Powering
Real-Time Systems of Engagement
Guest Speaker
Noel Yuhanna
Principal Analyst
Forrester Research
Brian Bulkowski
CTO and Co-Founder
Aerospike, Inc.
2Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]© 2016 FORRESTER. REPRODUCTION PROHIBITED.
3Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Database Trends Powering Real-Time Systems of
Engagement
Noel Yuhanna, Principal Analyst, Forrester Research
Aerospike Webinar
4Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Business growth and speed are
changing the way we access data…
5Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 5© 2016 FORRESTER. REPRODUCTION PROHIBITED.
We Are Moving From IT to Business Technology (BT)..
Trend
MIS
IT
BT
Self-service Real-time
Automation
Limited
data
Digital
business
Lots of
data
Batch
6Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 6© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Customer Lifecycle Is More Complex Than Ever
Social mediaChoices
Innovation
Lower cost
Support
Appeal
Blogs
Friends
Interact
7Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 7© 2016 FORRESTER. REPRODUCTION PROHIBITED.
TV
Email
Direct mail
Print
Out of home
Branch/store Call centers
Web
Social
Mobile
Customer Has Many Touch Points and Channels That Have Grown Over
The Years…
8Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 8© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Systems Of Engagement Directly Touches Customers
9Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 9© 2016 FORRESTER. REPRODUCTION PROHIBITED.
17
Age of the Customer is Driving the Need for Real-time Data Platform….
10Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 10© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Multi-dimensional View Of The Customer Drives Personalization
11Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 11© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Age of the Customer
How can you prevent members
from churning?
How can
you make
the
customer
experience
better?
How can you give the perfect
customer recommendation?
12Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 12© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Customer
insights
Online behavior
Social Data-as-a-service
Smart products Historical data
Scalable, low-cost, and elastic data platform
Mobile behavior and
context
We Need A Data Platform To Support Enhanced Customer Insights
13Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 13© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Real-time Requirements Have Grown
› No one needs yesterday day tomorrow!
› Competitive pressure – customer experience counts
› Run operational reporting and analytics as then happen
› New insights demand real-time data
› Real-time data helps win customers
› Technology is now mature to deliver real-time data platform
7
14Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 14© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Key Database trends Powering Real-time Systems of Engagement and
Digital Business Transformation
Leveraging
Memory and SSD NoSQL
Cloud
Database
25%
adoption
20%
adoption
35%
adoption
15Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 15© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Mobile applicationsReal-time analytics
Big data analyticsHigh-end transactional app
Packaged appsCustom apps
Scientific apps
Web apps
By 2018, 40% Enterprises Will Run Mission-critical Transactional &
Operational Apps With Memory Technology
16Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 16© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Real-time
Customer analytics
Systems of Engagement
Business transformation
CRM Logs, HadoopSocial media Clickstream
Hybrid Memory Database
EDW
Big
DataDB
Analytics
Apps Apps Insights
Hybrid Memory Delivers Faster Customer Insights, and Real-time Systems
of Engagement
17Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 17© 2016 FORRESTER. REPRODUCTION PROHIBITED.
•  Prevent customers from switching ..Keep customers
•  Recommendation engine
•  Search any data
Dazzle customers
•  Upsell or cross-sell new products.Sell more
•  Offer the customer specific discounts.Find opportunities
..bottom line it’ll help innovate, grow your company!
How organizations are Leveraging Hybrid Memory to Support Business
Transformation and SOE
18Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 18© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Recommendations
•  Use hybrid memory to innovate and become a
disruptor, there are endless possibilities
•  Intensify customer digital experiences
•  Insist on real-time analytics for various use
cases to gain competitive advantage
•  Look closely at vendor solutions that can scale,
deliver high performance are are lower cost
•  Focus on tiered memory –Dram, SSD/flash
•  Expand more use cases to drive business growth
IT
Business
19Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
FORRESTER.COM
Thank you
© 2016 FORRESTER. REPRODUCTION PROHIBITED.
Noel Yuhanna
www.forrester.com
Twitter: @nyuhanna
Thank you
20Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Hybrid Memory Databases for
Digital Transformation
Brian Bulkowski, CTO & Co-Founder, Aerospike, Inc.
21Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Hybrid Memory Architectures enable Digital
Transformation in fundamentally different ways. They
deliver:
•  Simplicity
•  Faster Time to Market
•  Business Agility
•  Competitive Advantage & lower TCO
Digital Transformation – The Next Wave
22Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Traditional Architecture Has Significant Limitations
Challenges
•  Complex
•  Maintainability
•  Durability
•  Consistency
•  Scalability
•  Cost ($)
•  Data Lag
Caching Layer
Operational Database
Real-time
Consumer Facing
Pricing /
Inventory/Billing
Real-time
Decisioning
Streaming
Data
Legacy Database
(Mainframe)
RDBMS
Database
Transactional
Systems
Enterprise Environment
Legacy RDBMS
HDFS BASED
Fast speed – Consumer Scale
23Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
What’s Needed – Hybrid Memory Database
High velocity of transactions
Targeted engagement requires large
numbers of transactions per second
Handle huge volumes of data
Must hold 100s of TBs per use case.
Non Volatile Memory (NVM)
Allows you to store large volumes of data
with extremely high performance &
consistency. Caching strategies routinely
fail with heavy write use cases.
Lower latency
Responses to queries must consistently
be less than 5 milliseconds.
Reliability
High availability – must be up 24 x 7.
No single point of failure.
Easy to scale & manage
Database must not require high amounts
of manual intervention.
Low cost of ownership
Need to reduce server “footprint”
while supporting many new use
cases.
Open & interoperable
Need to leverage existing
infrastructure & solutions.
24Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Hybrid Memory Architectures = Simplified Technology Stack
Aerospike
Connectors
Legacy Database
(Mainframe)
RDBMS
Database
Transactional
Systems
Enterprise Environment
XDR
Aerospike
Legacy RDBMS
HDFS BASED
Powered by High Performance NoSQL
Fast speed – Consumer Scale
Hybrid Memory Database
Benefits:
•  Simplicity
•  Maintainability
•  Durability
•  Consistency
•  Scalability
•  Cost ($)
•  Data Lag Reduced
Real-time
Consumer Facing
Pricing /
Inventory/Billing
Real-time
Decisioning
Streaming
Data
25Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
LEGACY DATABASE
(Mainframe)
XDR
App Servers
DATA WAREHOUSE/
DATA LAKE
LEGACY RDBMS
HDFS BASED
BUSINESS
TRANSACTIONS
Web views
( Payments/Fraud )
( Equity Trades )
( Recommendations )
( Real Time Billing )
High Performance Hybrid Memory DB
“REAL-TIME BIG DATA”
“DECISIONING”
500
Business Trans per sec
5000Calculations per sec
X = 2.5 M
Database Transactions per sec
Hybrid Memory DB’s at Operational Scale
26Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Hybrid Memory Database - Enabling Your Digital Transformation
Powered by High
Performance NoSQL
Aerospike – Hybrid Memory DB
NEXT GENERATION ARCHITECTURE
•  No cache required – simpler architecture!
•  Patented Flash Optimization – Log structured File System
•  Record Oriented, Schema Free NoSQL KV Store
PREDICTABLE PERFORMANCE
•  DRAM or Hybrid DRAM/Flash for Persistence
•  Stable, Low Latency and high throughput under any condition
•  Deployable on Bare Metal, virtualized, containerized, or Cloud
DYNAMIC CLUSTERING
•  Highest Uptime & Availability of any NoSQL (5 nines plus)
•  Automatic DB Cluster formation, healing and dynamic sharding
•  Cross Data Center Replication (XDR)
SMART APPS
•  Machine Learning
•  Broad language support (C/C++, Java,C#, Python, Go, Node.js, PHP)
•  Patented functionality, DB aware Clients
•  Rich API’s - Accelerated development
TCO
•  Optimized for Flash and DRAM
•  Demonstrated 10:1 price performance savings
•  Full Utilization ->10x reduction in servers deployed
•  Huge operational efficiency – “Set it and Forget it”
$
27Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Why Hybrid Memory Architecture Matters
28Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Competitive Enterprise Wins
Customer Situation Problem Aerospike Solution Customer Win
6th Largest
Brokerage
DB2+Gemfire cache
150 Servers growing to
1000
Single Aerospike cluster
– 12 servers
- $M in TCO Savings
- 99.9% of all transactions <1ms
Large Payments
Firm
2 ORCL RAC clusters
+ Terracotta cache
System Stability &
missing SLA’s
3 Aerospike Clusters –
20 Servers each
- Multi $M TCO Savings
- Significant improvement in SLA’s
Fraud/Digital
Identity Firm
DataStax/Cassandra
168 DataStax Servers
growing to 450+
30 Aerospike Servers –
2 clusters
- $3.25M in TCO Savings over 3 years
- Significant improvement in SLA’s
3rd Largest
Mobile Telco
ORCL Coherence /
DataStax Cassandra
Existing SOE solutions
unstable & Costly
5 POC’s against
Cassandra & ORCL
Coherence – all wins!
- Multi $M TCO Savings
- Significant improvement in SLA’s
Enterprise
Marketing
Automation Vendor
DataStax/Cassandra
PostgreSQL + cache
Hundreds of cache &
Cassandra Servers
Scalability challenges
Significant reduction of
server footprint – global
deployment
- Multi $M TCO Savings
- Significant improvement in SLA’s
29Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Use Cases
30Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
AdTech – Real-Time Bidding
Challenge
•  Low read latency (milliseconds)
•  100K to 5M operations/second
•  Ensure 100% uptime
•  Provide global data replication
Performance achieved
•  1 to 6 billion cookies tracked
•  5.0M auctions per second
•  100ms ad rendering, 50ms real-time bidding,
1ms database access
•  1.5KB median object size
Selected NoSQL
•  10X fewer nodes
•  10X better TCO
•  20X better read latency
•  High throughput at low latency
Ad is Displayed
Publishers
Ad Networks & SSPs
Ad Exchanges
Demand Side
Platform
Data Management
Platforms
Brands Agencies Buyers
0 ms 100 ms
31Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
A T M
CREDIT CARD
PROCESSING SYSTEM
FRAUD DETECTION &
PROTECTION APP
ACCOUNT
BEHAVIOR
ACCOUNT
STATISTICS
STATIC DATA
RULE 1 – PASSED ✔
RULE 2 – PASSED ✔
RULE 3 – FAILED ✗
HISTORICAL
DATA
RULES
RULE 1
RULE 2
RULE 3
…
Challenge
■  Overall SLA 750 ms
■  Loss of Business due to latency
■  Every Credit Card transaction requires
hundreds of DB reads/writes
Need to scale reliably
■  10 à 100 TB
■  10B à 100 B objects
■  200k à I Million+ TPS
Selected NoSQL
■  Built for Flash
■  Predictable Low latency at High Throughput
■  Immediate consistency, no data loss
■  Cross data center (XDR) support
■  20 Server Cluster
■  Dell 730xd w/ 4NVMe SSDs
Fraud Prevention
32Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Challenge
■  DB2 stores positions for 10 Million customers
■  Must update stock prices, show balances on 300 positions, process
250M transactions, 2 M updates/day
■  Running out of memory, data inconsistencies, restarts take 1 hour
■  150 Servers -> Growing to 1000
Need to scale reliably
■  3 à 13 TB
■  100 à 400 Million objects
■  200k à I Million TPS
Selected NoSQL
■  Built for Flash
■  Predictable Low latency at High Throughput
■  Immediate consistency, , no data loss
■  Cross data center (XDR) support
■  10 Server Cluster IBM DB2
(MAINFRAME)
Read/Write
Start of Day
Data Loading
End of Day
Reconciliation
Query
REAL-TIME
DATA FEED
ACCOUNT
POSITIONS
XDR
Fin Serv – Positions System of Record
33Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Challenge
•  Edge access to regulate traffic
•  Accessible using provisioning applications
(self-serve and through support personnel)
Need for Extremely High Availability,
Reliably, Low latency
•  > TBs of data
•  10-100M objects
•  10-200K TPS
Selected NoSQL
•  Clustered system
•  Predictable low latency at high throughput
•  Highly-available and reliable on failure
•  Cross data center (XDR) support
SOURCE
DEVICE/USER DESTINATIONReal-Time
Auth. QoS Billing
Request Execute
Request
Real-Time ChecksConfig Module App
Update Device
User Setting
Hot-Standby
XDR
Telco – Real-Time Billing and Charging Systems
34Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
Thank You!
35Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]
2017 DB Trends for Powering
Real-Time Systems of Engagement
Guest Speaker
Noel Yuhanna
Principal Analyst
Forrester Research
Brian Bulkowski
CTO and Co-Founder
Aerospike, Inc.

More Related Content

What's hot

ACID & CAP: Clearing CAP Confusion and Why C In CAP ≠ C in ACID
ACID & CAP:  Clearing CAP Confusion and Why C In CAP ≠ C in ACIDACID & CAP:  Clearing CAP Confusion and Why C In CAP ≠ C in ACID
ACID & CAP: Clearing CAP Confusion and Why C In CAP ≠ C in ACIDAerospike, Inc.
 
Tectonic Shift: A New Foundation for Data Driven Business
Tectonic Shift: A New Foundation for Data Driven BusinessTectonic Shift: A New Foundation for Data Driven Business
Tectonic Shift: A New Foundation for Data Driven BusinessAerospike, Inc.
 
Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...Ontico
 
How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)
How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)
How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)Ontico
 
Aerospike: The Enterprise Class NoSQL Database for Real-Time Applications
Aerospike: The Enterprise Class NoSQL Database for Real-Time ApplicationsAerospike: The Enterprise Class NoSQL Database for Real-Time Applications
Aerospike: The Enterprise Class NoSQL Database for Real-Time ApplicationsBrillix
 
IMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory Computing
IMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory ComputingIMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory Computing
IMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory ComputingIn-Memory Computing Summit
 
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
 
In memory computing principles by Mac Moore of GridGain
In memory computing principles by Mac Moore of GridGainIn memory computing principles by Mac Moore of GridGain
In memory computing principles by Mac Moore of GridGainData Con LA
 
Get Started with Data Science by Analyzing Traffic Data from California Highways
Get Started with Data Science by Analyzing Traffic Data from California HighwaysGet Started with Data Science by Analyzing Traffic Data from California Highways
Get Started with Data Science by Analyzing Traffic Data from California HighwaysAerospike, Inc.
 
Developing Software for Persistent Memory / Willhalm Thomas (Intel)
Developing Software for Persistent Memory / Willhalm Thomas (Intel)Developing Software for Persistent Memory / Willhalm Thomas (Intel)
Developing Software for Persistent Memory / Willhalm Thomas (Intel)Ontico
 
RedisConf17 - Redis Enterprise on IBM Power Systems
RedisConf17 - Redis Enterprise on IBM Power SystemsRedisConf17 - Redis Enterprise on IBM Power Systems
RedisConf17 - Redis Enterprise on IBM Power SystemsRedis Labs
 
MariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UN
MariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UNMariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UN
MariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UN✔ Eric David Benari, PMP
 
Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6DataStax
 
RedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ Memory
RedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ MemoryRedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ Memory
RedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ MemoryRedis Labs
 
How the Development Bank of Singapore solves on-prem compute capacity challen...
How the Development Bank of Singapore solves on-prem compute capacity challen...How the Development Bank of Singapore solves on-prem compute capacity challen...
How the Development Bank of Singapore solves on-prem compute capacity challen...Alluxio, Inc.
 
Aerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data DemystifiedAerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data DemystifiedOmid Vahdaty
 
SQream DB - Bigger Data On GPUs: Approaches, Challenges, Successes
SQream DB - Bigger Data On GPUs: Approaches, Challenges, SuccessesSQream DB - Bigger Data On GPUs: Approaches, Challenges, Successes
SQream DB - Bigger Data On GPUs: Approaches, Challenges, SuccessesArnon Shimoni
 
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...DataWorks Summit
 
How to Avoid Disasters via Software-Defined Storage Replication & Site Recovery
How to Avoid Disasters via Software-Defined Storage Replication & Site RecoveryHow to Avoid Disasters via Software-Defined Storage Replication & Site Recovery
How to Avoid Disasters via Software-Defined Storage Replication & Site RecoveryDataCore Software
 

What's hot (20)

ACID & CAP: Clearing CAP Confusion and Why C In CAP ≠ C in ACID
ACID & CAP:  Clearing CAP Confusion and Why C In CAP ≠ C in ACIDACID & CAP:  Clearing CAP Confusion and Why C In CAP ≠ C in ACID
ACID & CAP: Clearing CAP Confusion and Why C In CAP ≠ C in ACID
 
Tectonic Shift: A New Foundation for Data Driven Business
Tectonic Shift: A New Foundation for Data Driven BusinessTectonic Shift: A New Foundation for Data Driven Business
Tectonic Shift: A New Foundation for Data Driven Business
 
Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...
 
How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)
How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)
How to run Real Time processing on Big Data / Ron Zavner (GigaSpaces)
 
Aerospike: The Enterprise Class NoSQL Database for Real-Time Applications
Aerospike: The Enterprise Class NoSQL Database for Real-Time ApplicationsAerospike: The Enterprise Class NoSQL Database for Real-Time Applications
Aerospike: The Enterprise Class NoSQL Database for Real-Time Applications
 
IMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory Computing
IMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory ComputingIMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory Computing
IMCSummit 2015 - Day 2 General Session - Flash-Extending In-Memory Computing
 
Introduction to Aerospike
Introduction to AerospikeIntroduction to Aerospike
Introduction to Aerospike
 
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
 
In memory computing principles by Mac Moore of GridGain
In memory computing principles by Mac Moore of GridGainIn memory computing principles by Mac Moore of GridGain
In memory computing principles by Mac Moore of GridGain
 
Get Started with Data Science by Analyzing Traffic Data from California Highways
Get Started with Data Science by Analyzing Traffic Data from California HighwaysGet Started with Data Science by Analyzing Traffic Data from California Highways
Get Started with Data Science by Analyzing Traffic Data from California Highways
 
Developing Software for Persistent Memory / Willhalm Thomas (Intel)
Developing Software for Persistent Memory / Willhalm Thomas (Intel)Developing Software for Persistent Memory / Willhalm Thomas (Intel)
Developing Software for Persistent Memory / Willhalm Thomas (Intel)
 
RedisConf17 - Redis Enterprise on IBM Power Systems
RedisConf17 - Redis Enterprise on IBM Power SystemsRedisConf17 - Redis Enterprise on IBM Power Systems
RedisConf17 - Redis Enterprise on IBM Power Systems
 
MariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UN
MariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UNMariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UN
MariaDB 10.2 & MariaDB 10.1 by Michael Monty Widenius at Database Camp 2016 @ UN
 
Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6
 
RedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ Memory
RedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ MemoryRedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ Memory
RedisConf18 - Re-architecting Redis-on-Flash with Intel 3DX Point™ Memory
 
How the Development Bank of Singapore solves on-prem compute capacity challen...
How the Development Bank of Singapore solves on-prem compute capacity challen...How the Development Bank of Singapore solves on-prem compute capacity challen...
How the Development Bank of Singapore solves on-prem compute capacity challen...
 
Aerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data DemystifiedAerospike meetup july 2019 | Big Data Demystified
Aerospike meetup july 2019 | Big Data Demystified
 
SQream DB - Bigger Data On GPUs: Approaches, Challenges, Successes
SQream DB - Bigger Data On GPUs: Approaches, Challenges, SuccessesSQream DB - Bigger Data On GPUs: Approaches, Challenges, Successes
SQream DB - Bigger Data On GPUs: Approaches, Challenges, Successes
 
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...
 
How to Avoid Disasters via Software-Defined Storage Replication & Site Recovery
How to Avoid Disasters via Software-Defined Storage Replication & Site RecoveryHow to Avoid Disasters via Software-Defined Storage Replication & Site Recovery
How to Avoid Disasters via Software-Defined Storage Replication & Site Recovery
 

Viewers also liked

Aerospike: Key Value Data Access
Aerospike: Key Value Data AccessAerospike: Key Value Data Access
Aerospike: Key Value Data AccessAerospike, Inc.
 
Aerospike Hybrid Memory Architecture
Aerospike Hybrid Memory ArchitectureAerospike Hybrid Memory Architecture
Aerospike Hybrid Memory ArchitectureAerospike, Inc.
 
التفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباع
التفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباعالتفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباع
التفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباعsadikooo
 
From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...
From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...
From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...Stefan Pfeiffer
 
Creating Real-time Systems of Engagement with Analytics and Big Data
Creating Real-time Systems of Engagement with Analytics and Big DataCreating Real-time Systems of Engagement with Analytics and Big Data
Creating Real-time Systems of Engagement with Analytics and Big DataMongoDB
 
AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)
AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)
AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)Amazon Web Services
 
Oracle Database Mobile Server Performance Tuning
Oracle Database Mobile Server Performance TuningOracle Database Mobile Server Performance Tuning
Oracle Database Mobile Server Performance Tuningphilipploer
 
Moving from Records to Engagement to Insight
Moving from Records to Engagement to InsightMoving from Records to Engagement to Insight
Moving from Records to Engagement to InsightJohn Mancini
 
How to Get a Game Changing Performance Advantage with Intel SSDs and Aerospike
How to Get a Game Changing Performance Advantage with Intel SSDs and AerospikeHow to Get a Game Changing Performance Advantage with Intel SSDs and Aerospike
How to Get a Game Changing Performance Advantage with Intel SSDs and AerospikeAerospike, Inc.
 
Aerospike: Maximizing Performance
Aerospike: Maximizing PerformanceAerospike: Maximizing Performance
Aerospike: Maximizing PerformanceAerospike, Inc.
 
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/Hour
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/HourRunning a High Performance NoSQL Database on Amazon EC2 for Just $1.68/Hour
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/HourAerospike, Inc.
 
Configuring Aerospike - Part 2
Configuring Aerospike - Part 2 Configuring Aerospike - Part 2
Configuring Aerospike - Part 2 Aerospike, Inc.
 
Configuring Aerospike - Part 1
Configuring Aerospike - Part 1Configuring Aerospike - Part 1
Configuring Aerospike - Part 1Aerospike, Inc.
 
What the Spark!? Intro and Use Cases
What the Spark!? Intro and Use CasesWhat the Spark!? Intro and Use Cases
What the Spark!? Intro and Use CasesAerospike, Inc.
 
From distributed caches to in-memory data grids
From distributed caches to in-memory data gridsFrom distributed caches to in-memory data grids
From distributed caches to in-memory data gridsMax Alexejev
 
CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012
CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012
CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012Amazon Web Services
 

Viewers also liked (18)

Aerospike: Key Value Data Access
Aerospike: Key Value Data AccessAerospike: Key Value Data Access
Aerospike: Key Value Data Access
 
Redis vs Aerospike
Redis vs AerospikeRedis vs Aerospike
Redis vs Aerospike
 
Aerospike Hybrid Memory Architecture
Aerospike Hybrid Memory ArchitectureAerospike Hybrid Memory Architecture
Aerospike Hybrid Memory Architecture
 
التفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباع
التفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباعالتفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباع
التفرعات الرئيسية والعشائر المكونة لقبيلة الشرفاء أولاد أبي السباع
 
From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...
From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...
From Mass Marketing to 'Systems of Engagement' OR 10 Ingredients for Successf...
 
Creating Real-time Systems of Engagement with Analytics and Big Data
Creating Real-time Systems of Engagement with Analytics and Big DataCreating Real-time Systems of Engagement with Analytics and Big Data
Creating Real-time Systems of Engagement with Analytics and Big Data
 
AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)
AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)
AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)
 
Oracle Database Mobile Server Performance Tuning
Oracle Database Mobile Server Performance TuningOracle Database Mobile Server Performance Tuning
Oracle Database Mobile Server Performance Tuning
 
Moving from Records to Engagement to Insight
Moving from Records to Engagement to InsightMoving from Records to Engagement to Insight
Moving from Records to Engagement to Insight
 
How to Get a Game Changing Performance Advantage with Intel SSDs and Aerospike
How to Get a Game Changing Performance Advantage with Intel SSDs and AerospikeHow to Get a Game Changing Performance Advantage with Intel SSDs and Aerospike
How to Get a Game Changing Performance Advantage with Intel SSDs and Aerospike
 
in memory datenbanken
in memory datenbankenin memory datenbanken
in memory datenbanken
 
Aerospike: Maximizing Performance
Aerospike: Maximizing PerformanceAerospike: Maximizing Performance
Aerospike: Maximizing Performance
 
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/Hour
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/HourRunning a High Performance NoSQL Database on Amazon EC2 for Just $1.68/Hour
Running a High Performance NoSQL Database on Amazon EC2 for Just $1.68/Hour
 
Configuring Aerospike - Part 2
Configuring Aerospike - Part 2 Configuring Aerospike - Part 2
Configuring Aerospike - Part 2
 
Configuring Aerospike - Part 1
Configuring Aerospike - Part 1Configuring Aerospike - Part 1
Configuring Aerospike - Part 1
 
What the Spark!? Intro and Use Cases
What the Spark!? Intro and Use CasesWhat the Spark!? Intro and Use Cases
What the Spark!? Intro and Use Cases
 
From distributed caches to in-memory data grids
From distributed caches to in-memory data gridsFrom distributed caches to in-memory data grids
From distributed caches to in-memory data grids
 
CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012
CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012
CPN101 Revving up Your Applications - Compute - AWS re: Invent 2012
 

Similar to Database Trends Power Digital Transformation

SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORTSAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORTSybase Türkiye
 
Business Continuity Considerations for a More Reliable Postgres Environment
Business Continuity Considerations for a More Reliable Postgres EnvironmentBusiness Continuity Considerations for a More Reliable Postgres Environment
Business Continuity Considerations for a More Reliable Postgres EnvironmentEDB
 
Has Your Data Gone Rogue?
Has Your Data Gone Rogue?Has Your Data Gone Rogue?
Has Your Data Gone Rogue?Tony Pearson
 
Insights into Real-world Data Management Challenges
Insights into Real-world Data Management ChallengesInsights into Real-world Data Management Challenges
Insights into Real-world Data Management ChallengesDataWorks Summit
 
SAPPHIRENOW_2016_HDS_running_VMware V2.1
SAPPHIRENOW_2016_HDS_running_VMware V2.1SAPPHIRENOW_2016_HDS_running_VMware V2.1
SAPPHIRENOW_2016_HDS_running_VMware V2.1Frank Olszewski
 
Insights into Real World Data Management Challenges
Insights into Real World Data Management ChallengesInsights into Real World Data Management Challenges
Insights into Real World Data Management ChallengesDataWorks Summit
 
Turning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data PlatformTurning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data PlatformCloudera, Inc.
 
The Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data HubThe Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data HubCloudera, Inc.
 
Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...
Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...
Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...Senturus
 
SAP IQ 16 Product Annoucement
SAP IQ 16 Product AnnoucementSAP IQ 16 Product Annoucement
SAP IQ 16 Product AnnoucementDobler Consulting
 
Big Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on DataBig Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on DataMatt Stubbs
 
Big Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on DataBig Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on DataMatt Stubbs
 
Aerospike Meetup - Introduction - Ami - 04 March 2020
Aerospike Meetup - Introduction - Ami - 04 March 2020Aerospike Meetup - Introduction - Ami - 04 March 2020
Aerospike Meetup - Introduction - Ami - 04 March 2020Aerospike
 
DAT310_Which Database to Use When
DAT310_Which Database to Use WhenDAT310_Which Database to Use When
DAT310_Which Database to Use WhenAmazon Web Services
 
Capgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with ClouderaCapgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with ClouderaCapgemini
 
Data at the corner of SAP and AWS
Data at the corner of SAP and AWSData at the corner of SAP and AWS
Data at the corner of SAP and AWSOcean9, Inc.
 
Datameer6 for prospects - june 2016_v2
Datameer6 for prospects - june 2016_v2Datameer6 for prospects - june 2016_v2
Datameer6 for prospects - june 2016_v2Datameer
 
The new dominant companies are running on data
The new dominant companies are running on data The new dominant companies are running on data
The new dominant companies are running on data SnapLogic
 
Oracle presenatation a modern cloudis complete by design
Oracle presenatation   a modern cloudis complete by designOracle presenatation   a modern cloudis complete by design
Oracle presenatation a modern cloudis complete by designDr. Wilfred Lin (Ph.D.)
 
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...DataStax
 

Similar to Database Trends Power Digital Transformation (20)

SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORTSAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
 
Business Continuity Considerations for a More Reliable Postgres Environment
Business Continuity Considerations for a More Reliable Postgres EnvironmentBusiness Continuity Considerations for a More Reliable Postgres Environment
Business Continuity Considerations for a More Reliable Postgres Environment
 
Has Your Data Gone Rogue?
Has Your Data Gone Rogue?Has Your Data Gone Rogue?
Has Your Data Gone Rogue?
 
Insights into Real-world Data Management Challenges
Insights into Real-world Data Management ChallengesInsights into Real-world Data Management Challenges
Insights into Real-world Data Management Challenges
 
SAPPHIRENOW_2016_HDS_running_VMware V2.1
SAPPHIRENOW_2016_HDS_running_VMware V2.1SAPPHIRENOW_2016_HDS_running_VMware V2.1
SAPPHIRENOW_2016_HDS_running_VMware V2.1
 
Insights into Real World Data Management Challenges
Insights into Real World Data Management ChallengesInsights into Real World Data Management Challenges
Insights into Real World Data Management Challenges
 
Turning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data PlatformTurning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data Platform
 
The Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data HubThe Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data Hub
 
Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...
Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...
Leveraging the Cloud for BI Infrastructure: With Focus on and Demos of Micros...
 
SAP IQ 16 Product Annoucement
SAP IQ 16 Product AnnoucementSAP IQ 16 Product Annoucement
SAP IQ 16 Product Annoucement
 
Big Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on DataBig Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on Data
 
Big Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on DataBig Data LDN 2017: The New Dominant Companies Are Running on Data
Big Data LDN 2017: The New Dominant Companies Are Running on Data
 
Aerospike Meetup - Introduction - Ami - 04 March 2020
Aerospike Meetup - Introduction - Ami - 04 March 2020Aerospike Meetup - Introduction - Ami - 04 March 2020
Aerospike Meetup - Introduction - Ami - 04 March 2020
 
DAT310_Which Database to Use When
DAT310_Which Database to Use WhenDAT310_Which Database to Use When
DAT310_Which Database to Use When
 
Capgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with ClouderaCapgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with Cloudera
 
Data at the corner of SAP and AWS
Data at the corner of SAP and AWSData at the corner of SAP and AWS
Data at the corner of SAP and AWS
 
Datameer6 for prospects - june 2016_v2
Datameer6 for prospects - june 2016_v2Datameer6 for prospects - june 2016_v2
Datameer6 for prospects - june 2016_v2
 
The new dominant companies are running on data
The new dominant companies are running on data The new dominant companies are running on data
The new dominant companies are running on data
 
Oracle presenatation a modern cloudis complete by design
Oracle presenatation   a modern cloudis complete by designOracle presenatation   a modern cloudis complete by design
Oracle presenatation a modern cloudis complete by design
 
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
 

More from Aerospike, Inc.

Flash Economics and Lessons learned from operating low latency platforms at h...
Flash Economics and Lessons learned from operating low latency platforms at h...Flash Economics and Lessons learned from operating low latency platforms at h...
Flash Economics and Lessons learned from operating low latency platforms at h...Aerospike, Inc.
 
Storm Persistence and Real-Time Analytics
Storm Persistence and Real-Time AnalyticsStorm Persistence and Real-Time Analytics
Storm Persistence and Real-Time AnalyticsAerospike, Inc.
 
You Snooze You Lose or How to Win in Ad Tech?
You Snooze You Lose or How to Win in Ad Tech?You Snooze You Lose or How to Win in Ad Tech?
You Snooze You Lose or How to Win in Ad Tech?Aerospike, Inc.
 
Distributing Data The Aerospike Way
Distributing Data The Aerospike WayDistributing Data The Aerospike Way
Distributing Data The Aerospike WayAerospike, Inc.
 
Getting The Most Out Of Your Flash/SSDs
Getting The Most Out Of Your Flash/SSDsGetting The Most Out Of Your Flash/SSDs
Getting The Most Out Of Your Flash/SSDsAerospike, Inc.
 
Big Data Learnings from a Vendor's Perspective
Big Data Learnings from a Vendor's PerspectiveBig Data Learnings from a Vendor's Perspective
Big Data Learnings from a Vendor's PerspectiveAerospike, Inc.
 
Predictable Big Data Performance in Real-time
Predictable Big Data Performance in Real-timePredictable Big Data Performance in Real-time
Predictable Big Data Performance in Real-timeAerospike, Inc.
 

More from Aerospike, Inc. (7)

Flash Economics and Lessons learned from operating low latency platforms at h...
Flash Economics and Lessons learned from operating low latency platforms at h...Flash Economics and Lessons learned from operating low latency platforms at h...
Flash Economics and Lessons learned from operating low latency platforms at h...
 
Storm Persistence and Real-Time Analytics
Storm Persistence and Real-Time AnalyticsStorm Persistence and Real-Time Analytics
Storm Persistence and Real-Time Analytics
 
You Snooze You Lose or How to Win in Ad Tech?
You Snooze You Lose or How to Win in Ad Tech?You Snooze You Lose or How to Win in Ad Tech?
You Snooze You Lose or How to Win in Ad Tech?
 
Distributing Data The Aerospike Way
Distributing Data The Aerospike WayDistributing Data The Aerospike Way
Distributing Data The Aerospike Way
 
Getting The Most Out Of Your Flash/SSDs
Getting The Most Out Of Your Flash/SSDsGetting The Most Out Of Your Flash/SSDs
Getting The Most Out Of Your Flash/SSDs
 
Big Data Learnings from a Vendor's Perspective
Big Data Learnings from a Vendor's PerspectiveBig Data Learnings from a Vendor's Perspective
Big Data Learnings from a Vendor's Perspective
 
Predictable Big Data Performance in Real-time
Predictable Big Data Performance in Real-timePredictable Big Data Performance in Real-time
Predictable Big Data Performance in Real-time
 

Recently uploaded

Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsRoshan Dwivedi
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 

Recently uploaded (20)

Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 

Database Trends Power Digital Transformation

  • 1. 1Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 2017 DB Trends for Powering Real-Time Systems of Engagement Guest Speaker Noel Yuhanna Principal Analyst Forrester Research Brian Bulkowski CTO and Co-Founder Aerospike, Inc.
  • 2. 2Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]© 2016 FORRESTER. REPRODUCTION PROHIBITED.
  • 3. 3Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ]© 2016 FORRESTER. REPRODUCTION PROHIBITED. Database Trends Powering Real-Time Systems of Engagement Noel Yuhanna, Principal Analyst, Forrester Research Aerospike Webinar
  • 4. 4Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Business growth and speed are changing the way we access data…
  • 5. 5Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 5© 2016 FORRESTER. REPRODUCTION PROHIBITED. We Are Moving From IT to Business Technology (BT).. Trend MIS IT BT Self-service Real-time Automation Limited data Digital business Lots of data Batch
  • 6. 6Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 6© 2016 FORRESTER. REPRODUCTION PROHIBITED. Customer Lifecycle Is More Complex Than Ever Social mediaChoices Innovation Lower cost Support Appeal Blogs Friends Interact
  • 7. 7Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 7© 2016 FORRESTER. REPRODUCTION PROHIBITED. TV Email Direct mail Print Out of home Branch/store Call centers Web Social Mobile Customer Has Many Touch Points and Channels That Have Grown Over The Years…
  • 8. 8Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 8© 2016 FORRESTER. REPRODUCTION PROHIBITED. Systems Of Engagement Directly Touches Customers
  • 9. 9Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 9© 2016 FORRESTER. REPRODUCTION PROHIBITED. 17 Age of the Customer is Driving the Need for Real-time Data Platform….
  • 10. 10Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 10© 2016 FORRESTER. REPRODUCTION PROHIBITED. Multi-dimensional View Of The Customer Drives Personalization
  • 11. 11Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 11© 2016 FORRESTER. REPRODUCTION PROHIBITED. Age of the Customer How can you prevent members from churning? How can you make the customer experience better? How can you give the perfect customer recommendation?
  • 12. 12Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 12© 2016 FORRESTER. REPRODUCTION PROHIBITED. Customer insights Online behavior Social Data-as-a-service Smart products Historical data Scalable, low-cost, and elastic data platform Mobile behavior and context We Need A Data Platform To Support Enhanced Customer Insights
  • 13. 13Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 13© 2016 FORRESTER. REPRODUCTION PROHIBITED. Real-time Requirements Have Grown › No one needs yesterday day tomorrow! › Competitive pressure – customer experience counts › Run operational reporting and analytics as then happen › New insights demand real-time data › Real-time data helps win customers › Technology is now mature to deliver real-time data platform 7
  • 14. 14Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 14© 2016 FORRESTER. REPRODUCTION PROHIBITED. Key Database trends Powering Real-time Systems of Engagement and Digital Business Transformation Leveraging Memory and SSD NoSQL Cloud Database 25% adoption 20% adoption 35% adoption
  • 15. 15Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 15© 2016 FORRESTER. REPRODUCTION PROHIBITED. Mobile applicationsReal-time analytics Big data analyticsHigh-end transactional app Packaged appsCustom apps Scientific apps Web apps By 2018, 40% Enterprises Will Run Mission-critical Transactional & Operational Apps With Memory Technology
  • 16. 16Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 16© 2016 FORRESTER. REPRODUCTION PROHIBITED. Real-time Customer analytics Systems of Engagement Business transformation CRM Logs, HadoopSocial media Clickstream Hybrid Memory Database EDW Big DataDB Analytics Apps Apps Insights Hybrid Memory Delivers Faster Customer Insights, and Real-time Systems of Engagement
  • 17. 17Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 17© 2016 FORRESTER. REPRODUCTION PROHIBITED. •  Prevent customers from switching ..Keep customers •  Recommendation engine •  Search any data Dazzle customers •  Upsell or cross-sell new products.Sell more •  Offer the customer specific discounts.Find opportunities ..bottom line it’ll help innovate, grow your company! How organizations are Leveraging Hybrid Memory to Support Business Transformation and SOE
  • 18. 18Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 18© 2016 FORRESTER. REPRODUCTION PROHIBITED. Recommendations •  Use hybrid memory to innovate and become a disruptor, there are endless possibilities •  Intensify customer digital experiences •  Insist on real-time analytics for various use cases to gain competitive advantage •  Look closely at vendor solutions that can scale, deliver high performance are are lower cost •  Focus on tiered memory –Dram, SSD/flash •  Expand more use cases to drive business growth IT Business
  • 19. 19Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] FORRESTER.COM Thank you © 2016 FORRESTER. REPRODUCTION PROHIBITED. Noel Yuhanna www.forrester.com Twitter: @nyuhanna Thank you
  • 20. 20Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Hybrid Memory Databases for Digital Transformation Brian Bulkowski, CTO & Co-Founder, Aerospike, Inc.
  • 21. 21Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Hybrid Memory Architectures enable Digital Transformation in fundamentally different ways. They deliver: •  Simplicity •  Faster Time to Market •  Business Agility •  Competitive Advantage & lower TCO Digital Transformation – The Next Wave
  • 22. 22Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Traditional Architecture Has Significant Limitations Challenges •  Complex •  Maintainability •  Durability •  Consistency •  Scalability •  Cost ($) •  Data Lag Caching Layer Operational Database Real-time Consumer Facing Pricing / Inventory/Billing Real-time Decisioning Streaming Data Legacy Database (Mainframe) RDBMS Database Transactional Systems Enterprise Environment Legacy RDBMS HDFS BASED Fast speed – Consumer Scale
  • 23. 23Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] What’s Needed – Hybrid Memory Database High velocity of transactions Targeted engagement requires large numbers of transactions per second Handle huge volumes of data Must hold 100s of TBs per use case. Non Volatile Memory (NVM) Allows you to store large volumes of data with extremely high performance & consistency. Caching strategies routinely fail with heavy write use cases. Lower latency Responses to queries must consistently be less than 5 milliseconds. Reliability High availability – must be up 24 x 7. No single point of failure. Easy to scale & manage Database must not require high amounts of manual intervention. Low cost of ownership Need to reduce server “footprint” while supporting many new use cases. Open & interoperable Need to leverage existing infrastructure & solutions.
  • 24. 24Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Hybrid Memory Architectures = Simplified Technology Stack Aerospike Connectors Legacy Database (Mainframe) RDBMS Database Transactional Systems Enterprise Environment XDR Aerospike Legacy RDBMS HDFS BASED Powered by High Performance NoSQL Fast speed – Consumer Scale Hybrid Memory Database Benefits: •  Simplicity •  Maintainability •  Durability •  Consistency •  Scalability •  Cost ($) •  Data Lag Reduced Real-time Consumer Facing Pricing / Inventory/Billing Real-time Decisioning Streaming Data
  • 25. 25Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] LEGACY DATABASE (Mainframe) XDR App Servers DATA WAREHOUSE/ DATA LAKE LEGACY RDBMS HDFS BASED BUSINESS TRANSACTIONS Web views ( Payments/Fraud ) ( Equity Trades ) ( Recommendations ) ( Real Time Billing ) High Performance Hybrid Memory DB “REAL-TIME BIG DATA” “DECISIONING” 500 Business Trans per sec 5000Calculations per sec X = 2.5 M Database Transactions per sec Hybrid Memory DB’s at Operational Scale
  • 26. 26Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Hybrid Memory Database - Enabling Your Digital Transformation Powered by High Performance NoSQL Aerospike – Hybrid Memory DB NEXT GENERATION ARCHITECTURE •  No cache required – simpler architecture! •  Patented Flash Optimization – Log structured File System •  Record Oriented, Schema Free NoSQL KV Store PREDICTABLE PERFORMANCE •  DRAM or Hybrid DRAM/Flash for Persistence •  Stable, Low Latency and high throughput under any condition •  Deployable on Bare Metal, virtualized, containerized, or Cloud DYNAMIC CLUSTERING •  Highest Uptime & Availability of any NoSQL (5 nines plus) •  Automatic DB Cluster formation, healing and dynamic sharding •  Cross Data Center Replication (XDR) SMART APPS •  Machine Learning •  Broad language support (C/C++, Java,C#, Python, Go, Node.js, PHP) •  Patented functionality, DB aware Clients •  Rich API’s - Accelerated development TCO •  Optimized for Flash and DRAM •  Demonstrated 10:1 price performance savings •  Full Utilization ->10x reduction in servers deployed •  Huge operational efficiency – “Set it and Forget it” $
  • 27. 27Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Why Hybrid Memory Architecture Matters
  • 28. 28Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Competitive Enterprise Wins Customer Situation Problem Aerospike Solution Customer Win 6th Largest Brokerage DB2+Gemfire cache 150 Servers growing to 1000 Single Aerospike cluster – 12 servers - $M in TCO Savings - 99.9% of all transactions <1ms Large Payments Firm 2 ORCL RAC clusters + Terracotta cache System Stability & missing SLA’s 3 Aerospike Clusters – 20 Servers each - Multi $M TCO Savings - Significant improvement in SLA’s Fraud/Digital Identity Firm DataStax/Cassandra 168 DataStax Servers growing to 450+ 30 Aerospike Servers – 2 clusters - $3.25M in TCO Savings over 3 years - Significant improvement in SLA’s 3rd Largest Mobile Telco ORCL Coherence / DataStax Cassandra Existing SOE solutions unstable & Costly 5 POC’s against Cassandra & ORCL Coherence – all wins! - Multi $M TCO Savings - Significant improvement in SLA’s Enterprise Marketing Automation Vendor DataStax/Cassandra PostgreSQL + cache Hundreds of cache & Cassandra Servers Scalability challenges Significant reduction of server footprint – global deployment - Multi $M TCO Savings - Significant improvement in SLA’s
  • 29. 29Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Use Cases
  • 30. 30Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] AdTech – Real-Time Bidding Challenge •  Low read latency (milliseconds) •  100K to 5M operations/second •  Ensure 100% uptime •  Provide global data replication Performance achieved •  1 to 6 billion cookies tracked •  5.0M auctions per second •  100ms ad rendering, 50ms real-time bidding, 1ms database access •  1.5KB median object size Selected NoSQL •  10X fewer nodes •  10X better TCO •  20X better read latency •  High throughput at low latency Ad is Displayed Publishers Ad Networks & SSPs Ad Exchanges Demand Side Platform Data Management Platforms Brands Agencies Buyers 0 ms 100 ms
  • 31. 31Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] A T M CREDIT CARD PROCESSING SYSTEM FRAUD DETECTION & PROTECTION APP ACCOUNT BEHAVIOR ACCOUNT STATISTICS STATIC DATA RULE 1 – PASSED ✔ RULE 2 – PASSED ✔ RULE 3 – FAILED ✗ HISTORICAL DATA RULES RULE 1 RULE 2 RULE 3 … Challenge ■  Overall SLA 750 ms ■  Loss of Business due to latency ■  Every Credit Card transaction requires hundreds of DB reads/writes Need to scale reliably ■  10 à 100 TB ■  10B à 100 B objects ■  200k à I Million+ TPS Selected NoSQL ■  Built for Flash ■  Predictable Low latency at High Throughput ■  Immediate consistency, no data loss ■  Cross data center (XDR) support ■  20 Server Cluster ■  Dell 730xd w/ 4NVMe SSDs Fraud Prevention
  • 32. 32Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Challenge ■  DB2 stores positions for 10 Million customers ■  Must update stock prices, show balances on 300 positions, process 250M transactions, 2 M updates/day ■  Running out of memory, data inconsistencies, restarts take 1 hour ■  150 Servers -> Growing to 1000 Need to scale reliably ■  3 à 13 TB ■  100 à 400 Million objects ■  200k à I Million TPS Selected NoSQL ■  Built for Flash ■  Predictable Low latency at High Throughput ■  Immediate consistency, , no data loss ■  Cross data center (XDR) support ■  10 Server Cluster IBM DB2 (MAINFRAME) Read/Write Start of Day Data Loading End of Day Reconciliation Query REAL-TIME DATA FEED ACCOUNT POSITIONS XDR Fin Serv – Positions System of Record
  • 33. 33Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Challenge •  Edge access to regulate traffic •  Accessible using provisioning applications (self-serve and through support personnel) Need for Extremely High Availability, Reliably, Low latency •  > TBs of data •  10-100M objects •  10-200K TPS Selected NoSQL •  Clustered system •  Predictable low latency at high throughput •  Highly-available and reliable on failure •  Cross data center (XDR) support SOURCE DEVICE/USER DESTINATIONReal-Time Auth. QoS Billing Request Execute Request Real-Time ChecksConfig Module App Update Device User Setting Hot-Standby XDR Telco – Real-Time Billing and Charging Systems
  • 34. 34Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] Thank You!
  • 35. 35Proprietary & Confidential | © 2016 Aerospike Inc. All rights reserved.[ ] 2017 DB Trends for Powering Real-Time Systems of Engagement Guest Speaker Noel Yuhanna Principal Analyst Forrester Research Brian Bulkowski CTO and Co-Founder Aerospike, Inc.