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eXtremeDB
Financial Edition
FB lee.hyeongchae
hyeongchae @ G+
About me
 이너비트
 NHN ( CUBRID )
 텔코웨어
 알티베이스
▪ 티베로
▪ 리얼타임테크
▪ 아키스
▪ 선재소프트
McObject is ...
McObject Company
                   Telecom & Networking ↑
                   Aerospace & Defense
                   Consumer Electronics
                   Financial ↑
                   Industrial & Process Control
                   Energy & Smart Grid
                   Mobile Database
                   Telematics
                   Web services
                   (persistent memory caching)
                   Reference Applications
McObject President & CEO

               Steve T. Graves :
                Co-founder

               “In-memory database
               systems. Interview with
               Steve Graves, McObject.”
                – Roberto V. Zicari ( ODBMS )
Gartner
Massimo Pezzini :
The Next Generation
Architecture:
In-Memory Computing

Who's Who in In-Memory
DBMSs
 Published: 10. 09. 2012
 + McObject eXtremeDB
 + ALTIBASE HDB
DBMS2.com
Curt Monash :

Many kinds of memory-
centric data management


+ SAP HANA
+ IBM solidDB
+ McObject eXtremeDB
+ HP H-Store & VoltDB
+ Oracle TimesTen
(
           STAC®
    SECURITIES TECHNOLOGY ANALYSIS CENTER )
STAC Benchmark Council Members
                  McObject Joins
                  STAC Benchmark
                  Council – May 2012

                  DB Vendor :
                   1. KX Systems
                   2. McObject, LLC
STAC Workload Category


                As of 16.08.2010 :
                 Maket Data
                 Analytics
                 Execution
STAC Workload - Market Data
                                                                                                                       Examples of products
 Domain      Caption               Workload summary                                   Example metrics
                                                                                                                          to be tested*
                                                                            - Latency from exchange message hitting
                           Taking inbound market data messages                                                        Ticker plant software, ticker
                                                                            the wire to normalized update coming
            Direct feed    from                                                                                       plant appliances, full-service
STAC-M1     integration    exchanges, normalizing and caching them,
                                                                            through API
                                                                            - Max throughput to 5 clients with 99th
                                                                                                                      trading platforms that offer a
                           and making them available via an API.                                                      market data API
                                                                            percentile latency less than 1 ms
                                                                            - Latency from the moment a message is
                           Taking normalized market data streams            ready for distribution to the moment it
                                                                                                                      Market data platforms,
            Market data    through a publisher API and delivering           exits the subscriber API.
STAC-M2     distribution   them                                             - Latency to “undisturbed consumers”
                                                                                                                      messaging software, messaging
                                                                                                                      appliances
                           to multiple consumers via a subscriber API.      when other consumers are starved of
                                                                            resources
                                                                            - First-result latency
                           Querying a time-series dataset and
                                                                               (time to get back the first result)
            Time-series    applying
                                                                            - Last-result latency
STAC-M3     data
            management
                           various analytics. Taking streaming data,
                           applying basic analytics to it, and persisting
                                                                               (time to get back all results)
                                                                                                                      Tick databases
                                                                            - Write latency
                           it to a time-series store.
                                                                            - Storage efficiency
STAC Report: STAC-M3 / McObject eXtremeDB 5.0 /
         Kove XPD2 L2 / Dell / Mellanox (SUT: XTR121105)

▪ Type: Audited
▪ Specs: STAC-M3 Benchmarks (Antuco Suite)
▪ Stack under test:
 –   McObject eXtremeDB 5.0 Financial Edition
 –   Kove XPD™ L2 Storage System with Mellanox QDR InfiniBand, dual port
 –   Dell PowerEdge™ R910 Server
 –   Intel Xeon E7-4850 Processors
 –   CentOS Release 6.2 Final
 –   Mellanox MT26428 ConnectX-2 QDR InfiniBand, dual port HCA
 –   Mellanox MTS3600 InfiniScale-IV QDR InfiniBand switch
eXtremeDB 5.0 FE
           >=
   KDB+ 2.8
    STAC-M3 Report 4Q.2012
Key
eXtremeDB FE
  Features
eXtremeDB FE Architecture
▪ Core In-Memory Database System (IMDS) Design
  – As an in-memory database system (IMDS), eXtremeDB gives your application speed without rewrites
    or expensive new hardware.

▪ Short Execution Path, Tiny Footprint (Approximately 150K)
  – Small code size and minimal overhead (database system memory footprint is as small as 15% of
    managed data volume) means less RAM is required.

▪ Optional On-Disk or Hybrid Storage
  – McObject's eXtremeDB Fusion edition

▪ Columnar Layout for Time Series Data
  – Traditional DBMSs bring rows of data into L1/L2 cache for processing. But financial data – such as
    trades and quotes – is naturally columnar, and handled more efficiently by a column-based layout.
eXtremeDB FE Architecture

Mr. Simple !!

 Small !!
 Fast !!
 Reliable !!
By SQLite.org
Powerful Run-Time Features
ACID Transactions                            High Availability and Clustering
Transaction Logging                          64-Bit Support
Multi-Version Concurrency Control ( MVCC )   Open Replication
Cache Prioritization                         Event Notifications
Deterministic Rule-Based SQL Optimizer       Pattern Search
Security Features                            Binary Schema Evolution
Remote Procedure Calls ( RPCs )              Database Striping / Mirroring
XML Import / Export                          Kernel Mode Deployment
GUI-Based Performance Monitoring & API
Unmatched Developer Flexibility

                                     B-Tree, R-Tree, Patricia Trie, KD-Tree and
C/C++, SQL, JAVA, C# APIs
                                     hash Indexes

Wide Range of Supported Data Types   Designed To Prevent Database Corruption

Custom Collations                    Broad Platform Support

Source Code Available                Proven Solution

Unmatched Developer Support
Managing Market Data
with eXtremeDB Financial Edition

                    - Flexible data layout
                    - Vector-based statistical
                    function library
                      ( boolean, add, subract, multiply,
                    divide, compare, not, and, or, xor,
                    conversion, weighted sum, weighted
                    average, covariance, correlation,
                    conditional operations, difference,
                    concatenation, max, min, sum,
                    product, count, average, variance,
                    standard deviation, user-defined
                    functions and more… )
                    - Handles real-time and
                    historical data
ExtremeDB 4.5 FE



                     3G
              2.5G
         2G
    1G
Performance
eXtremeDB 5.0 FE
SUNJESOFT Gliese
  ALTIBASE XDB
ORACLE TimesTen
    2013, coming soon
WINNER
eXtremeDB 4.5 FE
      4Q.2012
Q?!A
FB lee.hyeongchae
hyeongchae @ G+
                    6:05:05 AM / 00

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eXtremeDB FE

  • 2. About me  이너비트  NHN ( CUBRID )  텔코웨어  알티베이스 ▪ 티베로 ▪ 리얼타임테크 ▪ 아키스 ▪ 선재소프트
  • 4. McObject Company Telecom & Networking ↑ Aerospace & Defense Consumer Electronics Financial ↑ Industrial & Process Control Energy & Smart Grid Mobile Database Telematics Web services (persistent memory caching) Reference Applications
  • 5. McObject President & CEO Steve T. Graves : Co-founder “In-memory database systems. Interview with Steve Graves, McObject.” – Roberto V. Zicari ( ODBMS )
  • 6. Gartner Massimo Pezzini : The Next Generation Architecture: In-Memory Computing Who's Who in In-Memory DBMSs Published: 10. 09. 2012 + McObject eXtremeDB + ALTIBASE HDB
  • 7. DBMS2.com Curt Monash : Many kinds of memory- centric data management + SAP HANA + IBM solidDB + McObject eXtremeDB + HP H-Store & VoltDB + Oracle TimesTen
  • 8. ( STAC® SECURITIES TECHNOLOGY ANALYSIS CENTER )
  • 9. STAC Benchmark Council Members McObject Joins STAC Benchmark Council – May 2012 DB Vendor : 1. KX Systems 2. McObject, LLC
  • 10. STAC Workload Category As of 16.08.2010 :  Maket Data  Analytics  Execution
  • 11. STAC Workload - Market Data Examples of products Domain Caption Workload summary Example metrics to be tested* - Latency from exchange message hitting Taking inbound market data messages Ticker plant software, ticker the wire to normalized update coming Direct feed from plant appliances, full-service STAC-M1 integration exchanges, normalizing and caching them, through API - Max throughput to 5 clients with 99th trading platforms that offer a and making them available via an API. market data API percentile latency less than 1 ms - Latency from the moment a message is Taking normalized market data streams ready for distribution to the moment it Market data platforms, Market data through a publisher API and delivering exits the subscriber API. STAC-M2 distribution them - Latency to “undisturbed consumers” messaging software, messaging appliances to multiple consumers via a subscriber API. when other consumers are starved of resources - First-result latency Querying a time-series dataset and (time to get back the first result) Time-series applying - Last-result latency STAC-M3 data management various analytics. Taking streaming data, applying basic analytics to it, and persisting (time to get back all results) Tick databases - Write latency it to a time-series store. - Storage efficiency
  • 12. STAC Report: STAC-M3 / McObject eXtremeDB 5.0 / Kove XPD2 L2 / Dell / Mellanox (SUT: XTR121105) ▪ Type: Audited ▪ Specs: STAC-M3 Benchmarks (Antuco Suite) ▪ Stack under test: – McObject eXtremeDB 5.0 Financial Edition – Kove XPD™ L2 Storage System with Mellanox QDR InfiniBand, dual port – Dell PowerEdge™ R910 Server – Intel Xeon E7-4850 Processors – CentOS Release 6.2 Final – Mellanox MT26428 ConnectX-2 QDR InfiniBand, dual port HCA – Mellanox MTS3600 InfiniScale-IV QDR InfiniBand switch
  • 13. eXtremeDB 5.0 FE >= KDB+ 2.8 STAC-M3 Report 4Q.2012
  • 14. Key eXtremeDB FE Features
  • 15. eXtremeDB FE Architecture ▪ Core In-Memory Database System (IMDS) Design – As an in-memory database system (IMDS), eXtremeDB gives your application speed without rewrites or expensive new hardware. ▪ Short Execution Path, Tiny Footprint (Approximately 150K) – Small code size and minimal overhead (database system memory footprint is as small as 15% of managed data volume) means less RAM is required. ▪ Optional On-Disk or Hybrid Storage – McObject's eXtremeDB Fusion edition ▪ Columnar Layout for Time Series Data – Traditional DBMSs bring rows of data into L1/L2 cache for processing. But financial data – such as trades and quotes – is naturally columnar, and handled more efficiently by a column-based layout.
  • 16. eXtremeDB FE Architecture Mr. Simple !! Small !! Fast !! Reliable !! By SQLite.org
  • 17. Powerful Run-Time Features ACID Transactions High Availability and Clustering Transaction Logging 64-Bit Support Multi-Version Concurrency Control ( MVCC ) Open Replication Cache Prioritization Event Notifications Deterministic Rule-Based SQL Optimizer Pattern Search Security Features Binary Schema Evolution Remote Procedure Calls ( RPCs ) Database Striping / Mirroring XML Import / Export Kernel Mode Deployment GUI-Based Performance Monitoring & API
  • 18. Unmatched Developer Flexibility B-Tree, R-Tree, Patricia Trie, KD-Tree and C/C++, SQL, JAVA, C# APIs hash Indexes Wide Range of Supported Data Types Designed To Prevent Database Corruption Custom Collations Broad Platform Support Source Code Available Proven Solution Unmatched Developer Support
  • 19. Managing Market Data with eXtremeDB Financial Edition - Flexible data layout - Vector-based statistical function library ( boolean, add, subract, multiply, divide, compare, not, and, or, xor, conversion, weighted sum, weighted average, covariance, correlation, conditional operations, difference, concatenation, max, min, sum, product, count, average, variance, standard deviation, user-defined functions and more… ) - Handles real-time and historical data
  • 20. ExtremeDB 4.5 FE 3G 2.5G 2G 1G
  • 22. eXtremeDB 5.0 FE SUNJESOFT Gliese ALTIBASE XDB ORACLE TimesTen 2013, coming soon