Uploaded byRobert Treat
Database Scalability Patterns
The document discusses various database scalability patterns, including vertical and horizontal scaling, read slaves, and multi-master configurations. It emphasizes the complexities and challenges of scaling, particularly focusing on write operations and the need for application changes. The significance of vertical scalability in both horizontally scaled systems and the costs associated with adding new nodes are also highlighted.
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Database Scalability Patterns
- 1. Database Scalability {Patterns} / Robert Treat Thursday, April 8, 2010
- 2. robert treat omniti postgres oracle - mysql mssql - sqlite -nosql Thursday, April 8, 2010
- 3. What are “DatabaseScalability Patterns?” Thursday, April 8, 2010
- 4. Part Design Patterns Part Application Life-Cycle Thursday, April 8, 2010
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- 9. Federated Data Storage “sharding” Horizontal Partitioning Read Slaves Multi-Master Horizontal Scaling Thursday, April 8, 2010
- 10. Read Slaves /Master - Slave Scale Read Load Thursday, April 8, 2010
- 11. Read Slaves /Master - Slave Scale Read Load • Typically • Full Copy of Data On Each Node • Asynchronous Thursday, April 8, 2010
- 12. Read Slaves /Master - Slave Scale Read Load • Typically • Consider • Full Copy of Data • Partial Copy On Each Node • Synchronous • Asynchronous • Don’t use a RDBMS? Thursday, April 8, 2010
- 13. Read Slaves /Master - Slave Scale Read Load • Typically • Consider • Full Copy of Data • Partial Copy On Each Node • Synchronous • Asynchronous • Don’t use a RDBMS? Requires Application Changes Thursday, April 8, 2010
- 14. Read Slaves /Master - Slave Scale Read Load • Typically • Consider • Full Copy of Data • Partial Copy On Each Node • Synchronous • Asynchronous • Don’t use a RDBMS? Requires Application Changes “easy” Thursday, April 8, 2010
- 15. Scaling Writes “not easy” Thursday, April 8, 2010
- 16. Multi-Master many different ways to implement this, few that actually work in production Thursday, April 8, 2010
- 17. Multi-Master many different ways to implement this, few that actually work in production write to any node, database syncs data Thursday, April 8, 2010
- 18. Multi-Master many different ways to implement this, few that actually work in production write to any node, database syncs data can reduce cpu, doesn’t reduce i/o Thursday, April 8, 2010
- 19. Multi-Master many different ways to implement this, few that actually work in production write to any node, database syncs data can reduce cpu, doesn’t reduce i/o failover solution not a scalability solution Thursday, April 8, 2010
- 20. Horizontal Partitioning • Divide schema by job operations • Move each piece to own server • Duplicate some data as needed Thursday, April 8, 2010
- 21. Horizontal Partitioning • Divide schema by job operations • Move each piece to own server • Duplicate some data as needed • You must separate dependencies in the app code first! Thursday, April 8, 2010
- 22. Horizontal Partitioning • Divide schema by job operations • Move each piece to own server • Duplicate some data as needed • You must separate dependencies in the app code first! Each node is a new instance of vertical scaling Thursday, April 8, 2010
- 23. Horizontal Scaling • data split across servers based on algorithm • data dropped into buckets (multiple?) • someone must keep track of data, and provide lookup services Thursday, April 8, 2010
- 24. Universal Truths ofScaling Databases Vertical Scalability is Helpful for Every Pattern Even in a horizontally scaled, fully distributed database, the number of nodes needed is affected by vertical scalability Thursday, April 8, 2010
- 25. Universal Truths ofScaling Databases New Nodes Are Never Free • Add points of failure • Add management costs • Add complexity to architecture • Add complexity to your app code Thursday, April 8, 2010
- 26. MyFirstDB V Vertical Partitioning V Vertical Scaling V Read Slaves V Horizontal Partitioning Thursday, April 8, 2010
- 27. plan for layereddata sources read / write connections in code use schemas to separate services Thursday, April 8, 2010
- 28. plan for layereddata sources read / write connections in code use schemas to separate services use postgres :-) Thursday, April 8, 2010
- 29. THANKS! more: xzilla.net @robtreat2 omniti.com Thursday, April 8, 2010