Data is stored as key-value pairs,
which are written to particular storage node(s), based on the hashed
value of the primary key.
provide highly reliable,
scalable and available,distributed storage
When to use noSQL Database
- where there are High read/writes
- Massive Data: For example, Google and Amazon have terabytes of data stored in big data centers. Querying and inserting is not performant in these scenarios because of the blocking/schema/transaction nature of the RDBMs. That's the reason they have implemented their own databases (actually, key-value stores) for massive performance gain and scalability.
- So much join for searching : your data makes no sense in SQL, you find yourself doing multiple JOIN queries for accessing some piece of information.
- you are breaking the relational model, you have CLOBs that store denormalized data and you generate external indexes to search that data.
- With some advanced planning, software updates and hardware upgrades can be performed while the database is still running hot. Try doing that with a relational database without taking it down, and you're in for a world of trouble.
- Scaling : NoSQL databases like Couchbase and 10Gen's MongoDB, he said, can be scaled up to handle much bigger data volumes with relative ease
When Not to Use NoSql Database
- If too much redudant huge volume data and needs fast search—go to Hadoop
- less relational data and scaling of data not needed : may be less than 1TB
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