This document discusses how NoSQL databases provide an alternative to traditional RDBMS for handling large datasets. It outlines the challenges of scaling relational databases and how NoSQL databases address issues of scalability, availability and speed through approaches like horizontal scaling, eventual consistency and schema flexibility. The document categorizes common NoSQL databases like key-value stores, document databases, graph databases and columnar databases and provides examples like MongoDB, Cassandra and Neo4j. While NoSQL databases are better suited to certain big data problems, the document also notes some limitations of NoSQL compared to SQL.

2. Web Scale with NoSQL Sergejus Barinovas(@sergejusb) http://sergejus.blogas.lt

3. Who Am I? Architect at Running NoSQL servers in production Blogger (http://sergejus.blogas.lt, @sergejusb) Community member (http://dotnetgroup.lt) Contact me via sergejus.barinovas@gmail.com

4. Powered by RDBMS Used everywhere… …even where it shouldn’t Used for 30+ years!

5. Back to 1980’s…

6. Data boom

7. in numbers 600 000 000 users 30 000 servers 20+ TB raw data per day >20 PB stored data

8. You really think they use RDBMS?

9. RDBMS Scaling Example

10. Simple usage Customers master Reads / Writes

11. Scale reads Customers master Writes Reads slave slave

12. Scale writes master Reads / Writes [N-Z] Customers [N-Z] master Customers [A-M] Reads / Writes [A-M]

13. Scale reads / writes slave slave Reads [A-M] master Customers [N-Z] Writes [N-Z] master Writes [A-M] Customers [A-M] Reads [A-M] slave slave

14. Pray your system won’t fail

15. Enter the NoSQL

16. Why NoSQL Limited SQL scalability Sharding and vertical partitioning Limited SQL availability Master / slave configuration Limited SQL speed of read operations Multiple read replicas SQL limitations for huge amount of data Key / value / type columns

17. NoSQLhistory 2009, Eric Evans, no:sql(est) NoSQL– open source distributed databases, not relational SQL databases NoSQL– not only SQL NoSQL-> Big Data

18. NoSQL characteristics (1/2) Scalability The ability to horizontally scale simple-operation throughput over many servers BASE A “weaker” concurrency model than the ACID transactions in most SQL systems

19. NoSQLcharacteristics (2/2) Distributed Efficient use of distributed indexes and RAM for data storage Schema-less The ability to dynamically define new attributes or data schema

20. ACID (transactions) Atomicity – all or nothing Consistency – state integrity Isolation – no reads of uncommitted data Durability – recover committed trans

21. CAP theorem 2000, Eric Brewer It is impossible for a distributed computer system to simultaneously provide all three of the following guarantees: Consistency Availability Partition tolerance

22. BASE (eventualconsistency) Basically – partial system failures are OKAvailable Soft state – inconsistency is OK Eventual consistency – stale data is OK

24. NoSQL Databases

25. NoSQLcategories Key / value store Document database Graph database Columnar database

26. Key / valuestore <key, value> or Tuple<key, v1,. ., vn> Simple operations Get Put Delete Key Value Byte[] Byte[]

27. Key / valuestore Key Value “current_date” 2011.04.04 “sergejusb” Binary Object “sergejusb” JSON Object

28. Key / value stores Redis (+)messaging (-)no shards Voldermort Membase (+)memcache interface Riak

29. Document database Document == complex object XML YAML JSON / BSON Support for secondary indexes Schema can be defined at runtime Optional support for simple querying using Map / Reduce

30. Document databases MongoDB (+)shards CouchDB (+)master / master replication

31. Graph database Graph == network Basic constructs Node Edge Properties sergejus.blogas.lt reads authors knows sergejus tdagys knows

32. Graph databases Neo4j (-)paid version required for scaling FlockDB (+)fast (-)limited functionality

33. Columnar database For HUGE amount of data Columns are added at a runtime Great scalability Horizontal Vertical

34. Columnar database Unusual data model Key Space ->Database Column Family -> Table Columns and Super Columns Super Column -> array of Columns Column -> Tuple<Key, Value, Timestamp, TTL>

35. Columnar database Simple column

36. Columnar database Simple column

37. Columnar database Cassandra (+)easy scalable HBase (+)consistent (+)part of Hadoop Hypertable

38. NoSQL is Cool! But…

40. NoSQL limitations ORDER BY ? Natural key order GROUP BY ? Map / Reduce* JOIN ? Multiple Map / Reduce* SELECT * ? Multi-machine Map / Reduce* *if possible

41. NoSQLLimitations Maturity Tooling Specificity

42. SQL vs. NoSQL Choose the right tool for the task You can use BOTH

43. Thank you! Sergejus Barinovas (@sergejusb) sergejus.barinovas@gmail.com http://sergejus.blogas.lt