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WHAT THE MARKET-LEADING DBMS VENDORS DON’T WANT YOU TO KNOW Disruption is gathering steam PowerPoint Presentation
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WHAT THE MARKET-LEADING DBMS VENDORS DON’T WANT YOU TO KNOW Disruption is gathering steam. Curt Monash. Analyst since 1981 Covered DBMS since the pre-relational days Also analytics, search, etc. Own firm since 1987 Publicly available research Feed at www.monash.com/signup.html

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WHAT THE MARKET-LEADING DBMS VENDORS DON’T WANT YOU TO KNOW Disruption is gathering steam


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    1. WHAT THE MARKET-LEADING DBMS VENDORS DON’T WANT YOU TO KNOW Disruption is gathering steam

    2. Curt Monash • Analyst since 1981 • Covered DBMS since the pre-relational days • Also analytics, search, etc. • Own firm since 1987 • Publicly available research • Feed at www.monash.com/signup.html • Blogs, including www.dbms2.com • White papers and more at www.monash.com

    3. Database diversity • Mike Stonebraker, PhD • “One size doesn’t fit all” • Curt Monash, PhD • “Horses for courses” • “Database diversity” • Mike and Curt • The world needs 9 to 11 different kinds of data management software

    4. Large enterprise DBMS portfolio • Principal OLTP/multipurpose DBMS • Principal OLAP DBMS • Midrange OLTP/multipurpose DBMS • Search • Legacy DBMS • Other specialty data management

    5. Midrange OTLP/multipurpose DBMS • “Standard editions” • Oracle, DB2, SQL*Server, Informix SE • Deliberately crippled • VAR-centric • Progress OpenEdge, Intersystems Cache’ • Accidentally crippled • “Open-source” • MySQL, EnterpriseDB

    6. OLTP DBMS worries Besides the greatest horror – data corruption – concerns include: • License/maintenance cost • Performance/scalability • Ease of administration • Ease of programming • Reliability/uptime • Security

    7. Three major kinds of transactions • Traditional business transactions • Orders • Employment changes • Compliance/risk monitoring • Simple events = sensors, logs, etc. • Web site clicks • Network events • Device monitoring • Vehicle monitoring • RFID • Content serving

    8. Traditional business transactions are • Complex • Consistent in the face of complexity • Stringently industrial-strength • Real business need • Customer expectations • Compliance

    9. Issues to consider for applications that record complex transactions • Schema complexity (integrity) • Schema variability • Peak performance • Uptime • Security

    10. Issues to consider for applications that record simple events • Performance • Uptime • What happens to the data next?

    11. Issues to consider for applications that serve content • Which datatypes? • Scale • The alphanumeric parts

    12. Application metrics • Peak concurrent update throughput • Query complexity and volume • Transaction (and constraint!) complexity • Overall database size (and change!) • Uptime requirements • Security/compliance requirements • Datatype needs

    13. And how will those evolve? Business model changes  Functional changes

    14. Environmental considerations • Hardware (SMP, blade, toy collection) • Middle tier • DBMS expertise (and where it sits in the organization) • Database administration tools • Development tools • Fixed-point applications (and how good is their generic JDBC/ODBC support?)

    15. And how will THOSE evolve? • Consolidation -- but what does that mean in your shop? • Modularity

    16. Example 1: Compliance/risk monitoring • Many feeder systems • One schema per feeder system • Accept both relational ETL and XML • Output via BI

    17. Key requirements 1 • Rigorous security • Easy administration • Eventual XML support • Unknown scalability

    18. Example 2: Contractually-defined products • Complex financial instruments • Vacations • Warranties

    19. Key requirements 2 • Strong native XML • Complex constraints • Availability • Security • Volume?

    20. Example 3: Content sharing and selling • Web-facing – video, music, photo, etc. • Internal content management

    21. Key requirements 3 • Performant media datatype support • Performant order entry • Performant user tracking and personalization • Spike scalability • 24/7 availability

    22. Major areas of OLTP DBMS differentiation • Performance and scaling • Administration and 24/7 operation • Constraints and referential integrity • Triggers and stored procedures • Datatype support

    23. Performance and scaling • Baseline, peak, future • For which features? • How sub-linear?

    24. Administration and uptime • Ongoing functions – backup, security, etc. • Indexes and mandatory maintenance?? • Replication, fail-over, etc.

    25. Database constraints • What can be done in theory? • Does it perform?

    26. Triggers and stored procedures • Performance • Languages • Automatic generation • Development, debugging, maintenance

    27. Datatype support • What do you need? • Performance • Datatype extensibility • (Where relevant) Quality of search

    28. Today’s main topics • You can and should use multiple DBMS • In particular, midrange OLTP DBMS are appealing • Not all midrange OLTP DBMS are created equal • Both application and environmental considerations are important • More info at www.monash.com and www.dbms2.com