SlideShare una empresa de Scribd logo
1 de 16
Descargar para leer sin conexión
1
16-Jun-18
Head of Sales @ VOLTDB jlee@VOLTDB.com +82 10 9196 1416
In-Memory based RDBMS / 100X Faster / ACID Transaction / Built-in HA / SQL+Java support
In-Memory
(FAST DATA) Event
2
“ In-Memory 기반 고성능 데이터베이스”
“초당 수백만건의 Streaming 데이터 처리 및 실시간 분석”
“ LG, 화웨이, 노키아, 미쯔비시 등 고객사 다수 “
“ 삼성전자를 포함해서 국내 고객사( )등에서
성능/기능 검증 됨”
▪ In-Memory
▪ Scale-Out, Shared Nothing Cluster
▪ Streaming
▪ Global - , LG, Huawei, Intel, Nokia, Mitsubishi
▪ IT / – Stock/IoT/Game/E-commerce
https://www.voltdb.com/
3 https://www.VOLTDB.com/resources/videos-technical/
FAST DATA ?
FAST DATA , BIG
DATA , Transaction , , ,
BIG DATA
4 https://www.VOLTDB.com/resources/videos-technical/
FAST DATA ?
FAST DATA Sensor , Transaction , ,
Event Event
Sensors
Click Streams
Machine Data
Data from
Device Events
Transactions
Customer
Interactions
(Ingestion)
(Analytics)
Export To BigData
FAST DATA Processing
5
VOLTDB
In-MemoryIn-MemoryIn-Memory
Export
ApplicationsMessageQueuesDataSources
…
Data Warehouse
▪ 100% In-Memory
▪ Scale-Out Cluster
▪ Shared Nothing Distributed
▪ ACID Relational Database SQL
▪ Event OLAP/Big Data
▪ Fast Data
▪ (Authorization) & (Authentication)
▪ (Personalization)
▪ / (Fraud Detection/Correction)
▪ Event
VOLTDB VOLTDB
Intelligence Feedback
6
VOLTDB
FAST DATA ACID SQL Relational DB(RDB)
Processing
Relational
State(RDB)VOLTDB
VOLTDB ACID In-Memory New SQL (RDB )
, FAST DATA
7
VOLTDB -
VOLTDB FAST DATA DB (NEW SQL)
8
Kafka / RabbitMQ
Storm, Flume, Sqoop
Storm +
Serving Layer
Spark +
Serving Layer
Cassandra, HBase
Hadoop, Message queues
VOLTDB - Open Source vs. VOLTDB
Applications, Message Queues, Data Sources
Ingest
Analyze Decide
• Counters
• Aggregations
• Time Series
• Statistics
• Store Results
• Query/Recombine
• Fast Serving
• Per-event policy
evaluations
• Responses
(synchronous)
• Side-effects
(asynchronous)
Export & Pipeline
Open-source
- Open-source -- FAST DATA / Generic -
9
Kafka / RabbitMQ
Ingest Interface
SQL, Java for Analytics Transactions / ACID
Hadoop, Message queues
- VOLTDB -- FAST DATA / Generic -
VOLTDB
VOLTDB - Open Source vs. VOLTDB
Applications, Message Queues, Data Sources
Ingest
Analyze Decide
• Counters
• Aggregations
• Time Series
• Statistics
• Store Results
• Query/Recombine
• Fast Serving
• Per-event policy
evaluations
• Responses
(synchronous)
• Side-effects
(asynchronous)
Export & Pipeline
10
Kafka / RabbitMQ
Ingest Interface
SQL, Java for Analytics Transactions / ACID
Hadoop, Message queues
Kafka / RabbitMQ
Storm, Flume, Sqoop
Storm +
Serving Layer
Spark +
Serving Layer
Cassandra, HBase
Hadoop, Message queues
- VOLTDB -- Open-source -
Component Transaction
vs.
VOLTDB - Open Source vs. VOLTDB
Opensource Component Interop
11
FAST DATA
VOLTDB
VOLTDB FAST DATA / Big Data
Ingest /
Interactive
Analytics
Decisioning
Fast Operational Database
Enterprise Apps
ETL
CRM ERP Etc.
Data Lake (HDFS)
BIG DATA
Non Relational
Processing
BI Reporting
Data Warehouse
Columnar
Analytics OLAP
Export
FAST DATA
DW EXPORT
DW
Materialized View
12
VOLTDB -
Real-time Analytics Transactions Transformations
• Materialized Views
• Capped Tables
• Ranking Indexes
• Per-event Java + SQL
• ACID processing
• Millisecond latency
responses.
• Loaders/Importers
• Export Connectors
• Sessionization
• Enrichment
VOLTDB Architecture
Commodity HW HA + ACID Scale-out VM-friendly
VOLTDB FAST DATA /
13
2014 ACM Turing Award
Mike Stonebraker
Stonebraker :
/
• In-Memory (durable to disk)
• Scale-out Shared-nothing
•
• Hadoop Data warehouse
• Open source
Cloud :
YCSB (Yahoo Cloud Serving Benchmark)
2.4m TPS
HERITAGE INNOVATION SUCCESS
14
▪ Michael Stonebraker
- RDBMS , 1973
Ingres & PostgreSQL
› UC Berkeley
- RDMS B-trees, Constraints, Trigger ,
Sybase, Microsoft SQL Server
- 2006 : “ DB
RDBMS Architect ”
- DB in-memory New
SQL (VOLTDB)
- , MIT
- Michael Stonebraker(Founder of VOLTDB)
15
- One transaction = One Client-DB
interaction
- Java Stored Procedures
Multi Statement Transaction
High-Velocity
In-Memory
ACID
SQL
In-Line
- Import
/ (analytics/decisions)
- Transaction
- Disk Durability
- RDBMS , 100x
H/W
- Scale Out -
-
-
- SQL
- Cluster
- Built-in Failover Replication
- Cloud
- Shared Nothing
VOLTDB
16

Más contenido relacionado

La actualidad más candente

Solving PostgreSQL wicked problems
Solving PostgreSQL wicked problemsSolving PostgreSQL wicked problems
Solving PostgreSQL wicked problemsAlexander Korotkov
 
PostgreSQL Streaming Replication Cheatsheet
PostgreSQL Streaming Replication CheatsheetPostgreSQL Streaming Replication Cheatsheet
PostgreSQL Streaming Replication CheatsheetAlexey Lesovsky
 
Building a fully managed stream processing platform on Flink at scale for Lin...
Building a fully managed stream processing platform on Flink at scale for Lin...Building a fully managed stream processing platform on Flink at scale for Lin...
Building a fully managed stream processing platform on Flink at scale for Lin...Flink Forward
 
Grafana optimization for Prometheus
Grafana optimization for PrometheusGrafana optimization for Prometheus
Grafana optimization for PrometheusMitsuhiro Tanda
 
Building an Activity Feed with Cassandra
Building an Activity Feed with CassandraBuilding an Activity Feed with Cassandra
Building an Activity Feed with CassandraMark Dunphy
 
20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...
20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...
20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...Umair Shahid
 
[112]rest에서 graph ql과 relay로 갈아타기 이정우
[112]rest에서 graph ql과 relay로 갈아타기 이정우[112]rest에서 graph ql과 relay로 갈아타기 이정우
[112]rest에서 graph ql과 relay로 갈아타기 이정우NAVER D2
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcachedJurriaan Persyn
 
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScale
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScaleThe Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScale
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScaleColin Charles
 
Using all of the high availability options in MariaDB
Using all of the high availability options in MariaDBUsing all of the high availability options in MariaDB
Using all of the high availability options in MariaDBMariaDB plc
 
Webinar: PostgreSQL continuous backup and PITR with Barman
Webinar: PostgreSQL continuous backup and PITR with BarmanWebinar: PostgreSQL continuous backup and PITR with Barman
Webinar: PostgreSQL continuous backup and PITR with BarmanGabriele Bartolini
 
Real-time Analytics with Trino and Apache Pinot
Real-time Analytics with Trino and Apache PinotReal-time Analytics with Trino and Apache Pinot
Real-time Analytics with Trino and Apache PinotXiang Fu
 
Using ScyllaDB for Distribution of Game Assets in Unreal Engine
Using ScyllaDB for Distribution of Game Assets in Unreal EngineUsing ScyllaDB for Distribution of Game Assets in Unreal Engine
Using ScyllaDB for Distribution of Game Assets in Unreal EngineScyllaDB
 
[pgday.Seoul 2022] PostgreSQL with Google Cloud
[pgday.Seoul 2022] PostgreSQL with Google Cloud[pgday.Seoul 2022] PostgreSQL with Google Cloud
[pgday.Seoul 2022] PostgreSQL with Google CloudPgDay.Seoul
 
2021.02 new in Ceph Pacific Dashboard
2021.02 new in Ceph Pacific Dashboard2021.02 new in Ceph Pacific Dashboard
2021.02 new in Ceph Pacific DashboardCeph Community
 
Timeseries - data visualization in Grafana
Timeseries - data visualization in GrafanaTimeseries - data visualization in Grafana
Timeseries - data visualization in GrafanaOCoderFest
 
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...Mihai Criveti
 
Intro ProxySQL
Intro ProxySQLIntro ProxySQL
Intro ProxySQLI Goo Lee
 
Apache HBase Improvements and Practices at Xiaomi
Apache HBase Improvements and Practices at XiaomiApache HBase Improvements and Practices at Xiaomi
Apache HBase Improvements and Practices at XiaomiHBaseCon
 

La actualidad más candente (20)

Solving PostgreSQL wicked problems
Solving PostgreSQL wicked problemsSolving PostgreSQL wicked problems
Solving PostgreSQL wicked problems
 
PostgreSQL Streaming Replication Cheatsheet
PostgreSQL Streaming Replication CheatsheetPostgreSQL Streaming Replication Cheatsheet
PostgreSQL Streaming Replication Cheatsheet
 
Building a fully managed stream processing platform on Flink at scale for Lin...
Building a fully managed stream processing platform on Flink at scale for Lin...Building a fully managed stream processing platform on Flink at scale for Lin...
Building a fully managed stream processing platform on Flink at scale for Lin...
 
Grafana optimization for Prometheus
Grafana optimization for PrometheusGrafana optimization for Prometheus
Grafana optimization for Prometheus
 
Building an Activity Feed with Cassandra
Building an Activity Feed with CassandraBuilding an Activity Feed with Cassandra
Building an Activity Feed with Cassandra
 
20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...
20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...
20230511 - PGConf Nepal - Clustering in PostgreSQL_ Because one database serv...
 
[112]rest에서 graph ql과 relay로 갈아타기 이정우
[112]rest에서 graph ql과 relay로 갈아타기 이정우[112]rest에서 graph ql과 relay로 갈아타기 이정우
[112]rest에서 graph ql과 relay로 갈아타기 이정우
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcached
 
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScale
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScaleThe Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScale
The Proxy Wars - MySQL Router, ProxySQL, MariaDB MaxScale
 
Using all of the high availability options in MariaDB
Using all of the high availability options in MariaDBUsing all of the high availability options in MariaDB
Using all of the high availability options in MariaDB
 
Webinar: PostgreSQL continuous backup and PITR with Barman
Webinar: PostgreSQL continuous backup and PITR with BarmanWebinar: PostgreSQL continuous backup and PITR with Barman
Webinar: PostgreSQL continuous backup and PITR with Barman
 
Real-time Analytics with Trino and Apache Pinot
Real-time Analytics with Trino and Apache PinotReal-time Analytics with Trino and Apache Pinot
Real-time Analytics with Trino and Apache Pinot
 
Using ScyllaDB for Distribution of Game Assets in Unreal Engine
Using ScyllaDB for Distribution of Game Assets in Unreal EngineUsing ScyllaDB for Distribution of Game Assets in Unreal Engine
Using ScyllaDB for Distribution of Game Assets in Unreal Engine
 
[pgday.Seoul 2022] PostgreSQL with Google Cloud
[pgday.Seoul 2022] PostgreSQL with Google Cloud[pgday.Seoul 2022] PostgreSQL with Google Cloud
[pgday.Seoul 2022] PostgreSQL with Google Cloud
 
Ansible
AnsibleAnsible
Ansible
 
2021.02 new in Ceph Pacific Dashboard
2021.02 new in Ceph Pacific Dashboard2021.02 new in Ceph Pacific Dashboard
2021.02 new in Ceph Pacific Dashboard
 
Timeseries - data visualization in Grafana
Timeseries - data visualization in GrafanaTimeseries - data visualization in Grafana
Timeseries - data visualization in Grafana
 
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...
 
Intro ProxySQL
Intro ProxySQLIntro ProxySQL
Intro ProxySQL
 
Apache HBase Improvements and Practices at Xiaomi
Apache HBase Improvements and Practices at XiaomiApache HBase Improvements and Practices at Xiaomi
Apache HBase Improvements and Practices at Xiaomi
 

Similar a VoltDB 소개

Building Fast Applications for Streaming Data
Building Fast Applications for Streaming DataBuilding Fast Applications for Streaming Data
Building Fast Applications for Streaming Datafreshdatabos
 
How to build streaming data applications - evaluating the top contenders
How to build streaming data applications - evaluating the top contendersHow to build streaming data applications - evaluating the top contenders
How to build streaming data applications - evaluating the top contendersAkmal Chaudhri
 
VoltDB Big Data Camp LA 2014 - Scott Jar
VoltDB  Big Data Camp LA 2014 - Scott JarVoltDB  Big Data Camp LA 2014 - Scott Jar
VoltDB Big Data Camp LA 2014 - Scott JarData Con LA
 
Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...
Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...
Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...NoSQLmatters
 
How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...
How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...
How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...VoltDB
 
Enabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical EnterpriseEnabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical EnterpriseHortonworks
 
VoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big Data
VoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big DataVoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big Data
VoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big DataVoltDB
 
Pivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream AnalyticsPivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream Analyticskgshukla
 
Fast Data – the New Big Data
Fast Data – the New Big DataFast Data – the New Big Data
Fast Data – the New Big DataVoltDB
 
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...VoltDB
 
Trafodion overview
Trafodion overviewTrafodion overview
Trafodion overviewRohit Jain
 
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016StampedeCon
 
Using real time big data analytics for competitive advantage
 Using real time big data analytics for competitive advantage Using real time big data analytics for competitive advantage
Using real time big data analytics for competitive advantageAmazon Web Services
 
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice MachineSpark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice MachineData Con LA
 
Middle Tier Scalability - Present and Future
Middle Tier Scalability - Present and FutureMiddle Tier Scalability - Present and Future
Middle Tier Scalability - Present and Futuredfilppi
 
Using a Fast Operational Database to Build Real-time Streaming Aggregations
Using a Fast Operational Database to Build Real-time Streaming AggregationsUsing a Fast Operational Database to Build Real-time Streaming Aggregations
Using a Fast Operational Database to Build Real-time Streaming AggregationsVoltDB
 
Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB
Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDBReal-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB
Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDBVoltDB
 
Real-time serverless analytics at Shedd – OLX data summit, Mar 2018, Barcelona
Real-time serverless analytics at Shedd – OLX data summit, Mar 2018, BarcelonaReal-time serverless analytics at Shedd – OLX data summit, Mar 2018, Barcelona
Real-time serverless analytics at Shedd – OLX data summit, Mar 2018, BarcelonaDobo Radichkov
 
Streaming Data and Stream Processing with Apache Kafka
Streaming Data and Stream Processing with Apache KafkaStreaming Data and Stream Processing with Apache Kafka
Streaming Data and Stream Processing with Apache Kafkaconfluent
 

Similar a VoltDB 소개 (20)

Building Fast Applications for Streaming Data
Building Fast Applications for Streaming DataBuilding Fast Applications for Streaming Data
Building Fast Applications for Streaming Data
 
How to build streaming data applications - evaluating the top contenders
How to build streaming data applications - evaluating the top contendersHow to build streaming data applications - evaluating the top contenders
How to build streaming data applications - evaluating the top contenders
 
VoltDB Big Data Camp LA 2014 - Scott Jar
VoltDB  Big Data Camp LA 2014 - Scott JarVoltDB  Big Data Camp LA 2014 - Scott Jar
VoltDB Big Data Camp LA 2014 - Scott Jar
 
Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...
Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...
Akmal Chaudhri - How to Build Streaming Data Applications: Evaluating the Top...
 
How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...
How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...
How to Build Real-Time Streaming Analytics with an In-memory, Scale-out SQL D...
 
Enabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical EnterpriseEnabling the Real Time Analytical Enterprise
Enabling the Real Time Analytical Enterprise
 
VoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big Data
VoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big DataVoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big Data
VoltDB and HPE Vertica Present: Building an IoT Architecture for Fast + Big Data
 
Pivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream AnalyticsPivotal Real Time Data Stream Analytics
Pivotal Real Time Data Stream Analytics
 
Fast Data – the New Big Data
Fast Data – the New Big DataFast Data – the New Big Data
Fast Data – the New Big Data
 
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...
VoltDB and Flytxt Present: Building a Single Technology Platform for Real-Tim...
 
Trafodion overview
Trafodion overviewTrafodion overview
Trafodion overview
 
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016
Best Practices For Building and Operating A Managed Data Lake - StampedeCon 2016
 
Using real time big data analytics for competitive advantage
 Using real time big data analytics for competitive advantage Using real time big data analytics for competitive advantage
Using real time big data analytics for competitive advantage
 
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice MachineSpark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
Spark as part of a Hybrid RDBMS Architecture-John Leach Cofounder Splice Machine
 
Middle Tier Scalability - Present and Future
Middle Tier Scalability - Present and FutureMiddle Tier Scalability - Present and Future
Middle Tier Scalability - Present and Future
 
Using a Fast Operational Database to Build Real-time Streaming Aggregations
Using a Fast Operational Database to Build Real-time Streaming AggregationsUsing a Fast Operational Database to Build Real-time Streaming Aggregations
Using a Fast Operational Database to Build Real-time Streaming Aggregations
 
Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB
Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDBReal-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB
Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB
 
Real-time serverless analytics at Shedd – OLX data summit, Mar 2018, Barcelona
Real-time serverless analytics at Shedd – OLX data summit, Mar 2018, BarcelonaReal-time serverless analytics at Shedd – OLX data summit, Mar 2018, Barcelona
Real-time serverless analytics at Shedd – OLX data summit, Mar 2018, Barcelona
 
Streaming Data and Stream Processing with Apache Kafka
Streaming Data and Stream Processing with Apache KafkaStreaming Data and Stream Processing with Apache Kafka
Streaming Data and Stream Processing with Apache Kafka
 
The CDO Agenda: how data architecture can help?
The CDO Agenda: how data architecture can help?The CDO Agenda: how data architecture can help?
The CDO Agenda: how data architecture can help?
 

Último

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Victor Rentea
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherRemote DBA Services
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Victor Rentea
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxRemote DBA Services
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistandanishmna97
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoffsammart93
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamUiPathCommunity
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesrafiqahmad00786416
 

Último (20)

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 

VoltDB 소개

  • 1. 1 16-Jun-18 Head of Sales @ VOLTDB jlee@VOLTDB.com +82 10 9196 1416 In-Memory based RDBMS / 100X Faster / ACID Transaction / Built-in HA / SQL+Java support In-Memory (FAST DATA) Event
  • 2. 2 “ In-Memory 기반 고성능 데이터베이스” “초당 수백만건의 Streaming 데이터 처리 및 실시간 분석” “ LG, 화웨이, 노키아, 미쯔비시 등 고객사 다수 “ “ 삼성전자를 포함해서 국내 고객사( )등에서 성능/기능 검증 됨” ▪ In-Memory ▪ Scale-Out, Shared Nothing Cluster ▪ Streaming ▪ Global - , LG, Huawei, Intel, Nokia, Mitsubishi ▪ IT / – Stock/IoT/Game/E-commerce https://www.voltdb.com/
  • 3. 3 https://www.VOLTDB.com/resources/videos-technical/ FAST DATA ? FAST DATA , BIG DATA , Transaction , , , BIG DATA
  • 4. 4 https://www.VOLTDB.com/resources/videos-technical/ FAST DATA ? FAST DATA Sensor , Transaction , , Event Event Sensors Click Streams Machine Data Data from Device Events Transactions Customer Interactions (Ingestion) (Analytics) Export To BigData FAST DATA Processing
  • 5. 5 VOLTDB In-MemoryIn-MemoryIn-Memory Export ApplicationsMessageQueuesDataSources … Data Warehouse ▪ 100% In-Memory ▪ Scale-Out Cluster ▪ Shared Nothing Distributed ▪ ACID Relational Database SQL ▪ Event OLAP/Big Data ▪ Fast Data ▪ (Authorization) & (Authentication) ▪ (Personalization) ▪ / (Fraud Detection/Correction) ▪ Event VOLTDB VOLTDB Intelligence Feedback
  • 6. 6 VOLTDB FAST DATA ACID SQL Relational DB(RDB) Processing Relational State(RDB)VOLTDB VOLTDB ACID In-Memory New SQL (RDB ) , FAST DATA
  • 7. 7 VOLTDB - VOLTDB FAST DATA DB (NEW SQL)
  • 8. 8 Kafka / RabbitMQ Storm, Flume, Sqoop Storm + Serving Layer Spark + Serving Layer Cassandra, HBase Hadoop, Message queues VOLTDB - Open Source vs. VOLTDB Applications, Message Queues, Data Sources Ingest Analyze Decide • Counters • Aggregations • Time Series • Statistics • Store Results • Query/Recombine • Fast Serving • Per-event policy evaluations • Responses (synchronous) • Side-effects (asynchronous) Export & Pipeline Open-source - Open-source -- FAST DATA / Generic -
  • 9. 9 Kafka / RabbitMQ Ingest Interface SQL, Java for Analytics Transactions / ACID Hadoop, Message queues - VOLTDB -- FAST DATA / Generic - VOLTDB VOLTDB - Open Source vs. VOLTDB Applications, Message Queues, Data Sources Ingest Analyze Decide • Counters • Aggregations • Time Series • Statistics • Store Results • Query/Recombine • Fast Serving • Per-event policy evaluations • Responses (synchronous) • Side-effects (asynchronous) Export & Pipeline
  • 10. 10 Kafka / RabbitMQ Ingest Interface SQL, Java for Analytics Transactions / ACID Hadoop, Message queues Kafka / RabbitMQ Storm, Flume, Sqoop Storm + Serving Layer Spark + Serving Layer Cassandra, HBase Hadoop, Message queues - VOLTDB -- Open-source - Component Transaction vs. VOLTDB - Open Source vs. VOLTDB Opensource Component Interop
  • 11. 11 FAST DATA VOLTDB VOLTDB FAST DATA / Big Data Ingest / Interactive Analytics Decisioning Fast Operational Database Enterprise Apps ETL CRM ERP Etc. Data Lake (HDFS) BIG DATA Non Relational Processing BI Reporting Data Warehouse Columnar Analytics OLAP Export FAST DATA DW EXPORT DW Materialized View
  • 12. 12 VOLTDB - Real-time Analytics Transactions Transformations • Materialized Views • Capped Tables • Ranking Indexes • Per-event Java + SQL • ACID processing • Millisecond latency responses. • Loaders/Importers • Export Connectors • Sessionization • Enrichment VOLTDB Architecture Commodity HW HA + ACID Scale-out VM-friendly VOLTDB FAST DATA /
  • 13. 13 2014 ACM Turing Award Mike Stonebraker Stonebraker : / • In-Memory (durable to disk) • Scale-out Shared-nothing • • Hadoop Data warehouse • Open source Cloud : YCSB (Yahoo Cloud Serving Benchmark) 2.4m TPS HERITAGE INNOVATION SUCCESS
  • 14. 14 ▪ Michael Stonebraker - RDBMS , 1973 Ingres & PostgreSQL › UC Berkeley - RDMS B-trees, Constraints, Trigger , Sybase, Microsoft SQL Server - 2006 : “ DB RDBMS Architect ” - DB in-memory New SQL (VOLTDB) - , MIT - Michael Stonebraker(Founder of VOLTDB)
  • 15. 15 - One transaction = One Client-DB interaction - Java Stored Procedures Multi Statement Transaction High-Velocity In-Memory ACID SQL In-Line - Import / (analytics/decisions) - Transaction - Disk Durability - RDBMS , 100x H/W - Scale Out - - - - SQL - Cluster - Built-in Failover Replication - Cloud - Shared Nothing VOLTDB
  • 16. 16