This document discusses NoSQL and the CAP theorem. It begins with an introduction of the presenter and an overview of topics to be covered: What is NoSQL and the CAP theorem. It then defines NoSQL, provides examples of major NoSQL categories (document, graph, key-value, and wide-column stores), and explains why NoSQL is used, including to handle large, dynamic, and distributed data. The document also explains the CAP theorem, which states that a distributed data store can only satisfy two of three properties: consistency, availability, and partition tolerance. It provides examples of how to choose availability over consistency or vice versa. Finally, it concludes that both SQL and NoSQL have valid use cases and a combination

1. What is NoSQL and
CAP Theorem
June 2014 NoSQL Meetup
Rahul Jain
@rahuldausa

2. Who am I ?
 Software Engineer
 7 years of software development experience
 Areas of expertise/interest
 High traffic web applications
 JAVA/J2EE
 Big data, NoSQL
 Information-Retrieval, Machine learning
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3. Agenda
• What is NoSQL
• CAP Theorem
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4. NoSQL Not SQL
does not mean

5. NoSQL Not Only SQL
OR
Not Relational DatabaseIt means

6. Why NoSQL
• Large Volume of Data
• Dynamic Schemas
• Auto-sharding
• Replication
• Horizontally Scalable
* Some Operations can be achieved by Enterprise class RDBMS software but with very High cost

7. Major NoSQL Categories
• Document databases
• pair each key with a complex data structure
known as a document.
• MongoDB
• Graph databases
• store information about networks, such as social
connections
• Neo4j
Contd.

8. Major NoSQL Categories
• Key-Value stores
• Every single item in the database is stored as an
attribute name (or "key"),
• Riak , Voldemort, Redis
• Wide-column stores
• store data in columns together, instead of row
• Google’s Bigtable, Cassandra and HBase

9. CAP Theorem

10. CAP Theorem
• Consistency
– All the servers in the system will have the same data
so anyone using the system will get the same copy
regardless of which server answers their request.
• Availability
– The system will always respond to a request (even if
it's not the latest data or consistent across the system
or just a message saying the system isn't working)
• Partition Tolerance
– The system continues to operate as a whole even if
individual servers fail or can't be reached..

11. Credit: http://architects.dzone.com/articles/better-explaining-cap-theorem

12. Choosing AP
Credit: https://foundationdb.com/key-value-store/white-papers/the-cap-theorem

13. Choosing CP
Credit: https://foundationdb.com/key-value-store/white-papers/the-cap-theorem
Replication allows to
add Availability

14. Finally …
SQL
Works great, but can’t fit for large dataset
NoSQL
Works great, but can’t fit for all Use-cases
SQL + NoSQL

15. Thanks!
@rahuldausa on twitter and slideshare
http://www.linkedin.com/in/rahuldausa
Interested in Search/Information Retrieval ?
Join us @ http://www.meetup.com/Hyderabad-Apache-Solr-Lucene-Group/
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