BigData - Hadoop Training in Chennai - 09789968765

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NoSQL databases have a lot more to offer than just solving the problems of scale which are mentioned as follows:

Schemaless data representation: Almost all NoSQL implementations offer schemaless data representation. This means that you don’t have to think too far ahead to define a structure and you can continue to evolve over time—including adding new fields or even nesting the data, for example, in case of JSON representation.
Development time: I have heard stories about reduced development time because one doesn’t have to deal with complex SQL queries. Do you remember the JOIN query that you wrote to collate the data across multiple tables to create your final view?
Speed: Even with the small amount of data that you have, if you can deliver in milliseconds rather than hundreds of milliseconds—especially over mobile and other intermittently connected devices—you have much higher probability of winning users over.
Plan ahead for scalability: You read it right. Why fall into the ditch and then try to get out of it? Why not just plan ahead so that you never fall into one. Or in other words, your application can be quite elastic—it can handle sudden spikes of load. Of course, you win users over straightaway.

NoSQL is a generic term used to refer to any data store that does not follow the traditional RDBMS model—specifically, the data is non-relational and it does not use SQL as the query language. It is used to refer to the databases that attempt to solve the problems of scalability and availability against that of atomicity or consistency.

NoSQL is not a database. It is not even a type of database. In fact, it is a term used to filter out (read reject) a set of databases out of the ecosystem. There are several distinct family trees available. In Chapter 4, Advantages and Drawbacks, we explore various types of data models (or simply, database types) available under this umbrella.

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