The document discusses the hype around NoSQL databases and provides guidance on selecting the right database solution. It summarizes different database types and evaluates databases based on characteristics like concurrency control, data storage, replication, and transaction support. The document advises profiling applications carefully before selecting a database and avoiding premature decoupling of data.

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

9. Are active projects

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