The document discusses the differences between relational database management systems (RDBMS) and NoSQL databases. RDBMS uses ACID properties and SQL but does not scale well horizontally. NoSQL databases sacrifice ACID compliance for improved scalability and can handle massive loads. Common NoSQL database types include key-value stores, document databases, wide column stores, and graph databases. NoSQL databases have flexible, schema-less data models and eventually consistent designs that prioritize availability over strong consistency.

1. what’s under the hood? Aleksey Solntsev

2. The Digital Universe

3. Some facts

4. What’s they have in common? Performance Scalability Price

5. RDBMS ACID doesn’t scale well horizontally Shardingbreaks relations Joins are inefficient Transactions overhead Schema is not flexible

7. Consistency

8. Isolation

10. We need to scale!

11. Replication aka RAID1

12. Sharding aka RAID0

13. CAP theorem (Brewer's theorem)

15. Consistency

16. Isolation

18. Soft State

20. NoSQL Taxonomy Key Value / Tuple Store Eventually Consistent Key Value Store Wide Column Store / Column Families Document Oriented XML Databases Object Databases Graph Databases

23. Partitioning 1/2

24. Partitioning 2/2

25. Primitive API CRUD

26. Map/Reduce for aggregation map(String filename, String document) { List<String> T = tokenize(document); for each token in T { emit ((String)token, (Integer) 1); } } reduce(String token, List<Integer> values) { Integer sum = 0; for each value in values { sum = sum + value; } emit ((String)token, (Integer) sum); }

27. MapReduceи Hadoop?

30. SuperColumn

31. ColumnFamily

32. Keyspace

34. API No standards: Structure manipulation Cluster administration Query language

36. Document versioning

38. Advances Query API Find by example db.stat.find({clicks: {$gt: 10} }); Find & sort db.users.find({}).sort({name: 1}); Skip & limit db.users.find().skip(20).limit(10);

39. @a_solntsev