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Replication for real-time warehousing

Replication for real-time warehousing. Philip Howard Research Director – Bloor Research. Agenda. What is data replication? When would you use it? What are its requirements? Putting it into context. What is data replication?.

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Replication for real-time warehousing

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  1. Replication for real-time warehousing Philip Howard Research Director – Bloor Research

  2. Agenda • What is data replication? • When would you use it? • What are its requirements? • Putting it into context

  3. What is data replication? “The process of copying a portion of a data sourcefrom one environment to another and keeping the subsequent copies of the data in sync with the original source. Changes made to the original source are propagated to the copies of the data in other environments.”

  4. When would you use data replication? • Data warehousing and BI • Loading real-time data for operational BI • Supporting real-time query/reporting • Integrating CEP with operational data • Operational synchronisation • e.g. Lookers v Bookers • e.g. synchronising (POS and) central pricing data • High/continuous availability • Data migration (zero downtime) • Master data management • To update/broadcast from a hub • High/continuous availability • …

  5. Enabling data replication • Performance • Native interfaces • Support for parallelism • Compression • Change data capture • Impact minimalism • Heterogeneity • Topology support • Synchronisation • Graphical development and management/monitoring • In operational/HA environments: transactional integrity

  6. Performance 1: native interfaces High level interfaces (O/JDBC) not fast enough

  7. But …

  8. Performance 2: parallelism

  9. Performance 3: compression One size does not fit all

  10. Performance 4: CDC

  11. But …

  12. Performance 5: impact minimalism

  13. Heterogeneity

  14. Big Data

  15. Topology support 1 to 1 1 to Many Many to 1 M to M 1 to 1 to 1 etc

  16. Synchronisation

  17. Development & Monitoring

  18. Development & Monitoring

  19. Data Replication in context

  20. Data Replication in context Copies data in real-time, simple transformations Leaves data in situ Transforms data and moves it in real-time/batch

  21. Data Replication in context

  22. Conclusion • Replication serves sundry purposes • Fastest growing adoption for BI • Key requirement is performance but multiple others • Complementary (not competitive) to both data integration and data virtualisation

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