Comparison between RDBMS and Map-Reduce

	RDBMS	Map-Reduce
Scalability	Scale UP	Scale Out
Data Size	GB	PB and more
Read/Write	Batch and Interactive	Batch
Update Type	Write many Read many	Write once Read many
Integrity	High	Low
Structure	Structural data/ Schema first Write later	Non Structural data/ Write first Schema later
Query	SQL	No SQL and SQL support too with add on tools
Response time	Faster for Less data/ slow once size increases	Faster for more data in comparison
Note: Slowly with the new sub projects being developed for Hadoop this gap is being filled up as people are developing an abstract layer on top of Map-Reduce and YARN frameworks which takes SQL and in turn convert it to Map-Reduce/Yarn.

Working with NoSQL Databases

How to get started with NoSQL?

Since 2009 NoSQL databases becomes more and more popular. But why?

• No usage of SQL, that means
  • Less complexity
  • Better portability
  • Boundlessness
  • User-friendliness
• Most databases are Open-Source
• Performance
• Scalability

Famous companies like Twitter, Facebook and Amazon are using NoSQL databases.
What sorts of NoSQL databases are used today?

• Key-Value stores
  • Easy to implement
  • Only key-value-pairs can be stored
  • Difficult to build complex data structures
• Column stores
  • Columns don't have to be defined in advance.
  • A row can have different numbers of cells
• Document stores
  • Like key-value stores, but allows nested values
• Graph databases
  • Objects and relationships are modelled and persisted as nodes and edges of a graph

What NoSQL databases are present today?