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Databases benoitg 2009-03-10
- 1. Making sense in the brave new world of databases Benoit Grégoire Savoir-faire Linux [email_address]
- 2. Why am I here? The last time SQL was declared dead wasn't fun.
- 3. There is this new hype called “NoSql”
- 4. I don't want to deal with another database holy war for the next ten years of my career. Especially if it will prevent us from using the right tool for the job.
- 5. Lots of smart people worked on new tools, but fanboys are beginning to strike...
- 6. Typical decision criteria Criteria 1: Is it popular/hyped?
- 7. There is no criteria 2
- 8. What did I do Survey all databases that: Are OSS
- 10. Why are you here Nobody needs this theorical mumbo-jumbo, right?
- 11. Rumor has is Google has a few PHD on it's payroll
- 12. The problem: The typical web developer's entire Database training is: I use MySql
- 13. I overheard it has a manual, but I didn't actually check since I use an ORM for everything.
- 14. ORMs probably did more damage to database understading than any other factor. Not understanding the fundamental caracteristics of the database system prevents you from making good decisions
- 15. Relational databases aren't the only option. If you go through the pain of using an ORMs, you need to at least want SOMETHING from relational databases: SQL
- 16. Transactions
- 17. Relational integrity and schema enforcement
- 18. Fast joins WITHOUT instanciating objects
- 19. Replication (but then you probably chose the wrong solution)
- 20. So if not NoSQL, then what High Performance Scalable Data Stores (HPSDS)
- 21. Scalable Non Relational Database (SNRD?)
- 22. The movement formerly known as NoSQL?
- 23. Databases
- 24. Internet scale It's great that it's possible
- 25. Most web applications are not
- 26. Those that are don't have all of their components « Internet scale »
- 27. Plan for it, but you probably don't need it NOW. Google didn'T start with BigTable and MapReduce...
- 28. Major problem: Scaling Read scaling Comparatively easy Write scaling Much harder Computational scalling Not historically part of database feature lists
- 29. Major problem: Availability and replication
- 30. Major problem: Transactions
- 31. Traditional databases: ACID Atomicity
- 32. Consistency
- 33. Isolation
- 34. Durability
- 35. Life is about compromises So is computing
- 36. Good – Fast – Cheap
- 38. Brewer's CAP Theorem (2000) In a distributed system, chose any two of: Consistency
- 39. Availability
- 40. Partition Tolerance No set of failures less than total network failure is allowed to cause the system to respond incorrectly (Gilbert & Lynch)
- 41. Latency is all important And unavoidable (the speed of light is unlikely to change) Montreal Sydney round-trip IS going to take 130ms
- 42. Unless maybe...
- 44. Soft-state
- 46. Classyfying databases is difficult There are projects trying to be more than one basic type (ModetDB, Virtuoso)
- 47. Some of them use another as backend or frontend
- 48. Selection criterias Open source
- 49. Active project
- 53. Key-Value stores
- 55. Graph databases
- 58. Object databases
- 59. What about Map-Reduce? Classical distributed computing: Move program and data to processing nodes Map-Reduce Move program to the data node
- 60. Comparing curency/locks/transactions Conc Control Data storage Replication Txn Redis Locks RAM Async N Scalaris Locks RAM Sync L Tokyo Locks RAM or disk Async L Voldemort MVCC RAM or BDB Async N SimpleDB None S3 Async N Riak MVCC Pluggable Async N MongoDB Field-level Disk Async N Couch DB MVCC Disk Async N HBase Locks Hadoop Async L HyperTable Locks Files Sync L Cassandra MVCC Disk Async L BigTable Locks + stamps GFS Sync + Async L ScaleDB Locks Disk Sync Y MySQL Cluster Locks Disk or RAM Sync Y MySql MyIsam Locks Disk Async N MySQL InnoDB MVCC Disk Async Y Drizzle Locks Disk Sync Y PostgreSQL MVCC Disk Pluggable Y
- 61. How early should you try to decouple your data? Spliting data is more difficult than spliting applications
- 62. Are we headed to the one database to rule them all?
- 63. Closing thoughts Profile, profile, profile
- 64. Don't neglect local caching
- 65. A database is not something that can be abstracted out.