Relational many of the cases, how the use of

Relational databases depends on tables, columns, rows or schemas to arrange systematically the data and retrieve it. A NoSQL originally refers to non-Structured Query Language or  non relational database giving a structure for storing and getting data that is presented in means other than the tabular form or relations likewise used in “relational databases”. Such databases existed from late 90’s, but didn’t obtain the  NoSQL brand until a rise of popularity in the early twenty-first century, caused by the needs of Web 2.0 companies such as Yahoo, Facebook, Google, and Amazon. NoSQL databases are increasingly used in big data and real-time web applications. These are also called Not only SQL for the fact that they may support SQL-like query languages.Why the need of NoSQL?RDBMSs operate with a relational model defined by schema, where each table is a strictly defined collection of rows and columns and a relationship can then be established between each row in one table and a row in another table. Relational data can be queried and manipulated by using SQL query language. To prevent the inconvenience to store data in the form of tables or we have other kind of relationships between records and want to quickly access the data.Why nosql preferred over sql :- In many of the cases, how the use of RDBMSs leads to problems due to fixed schema, which makes them ill-suited for changing business requirements, as schema changes are problematic and time-consuming, causing insufficient performance and latency for the new requirements and limited ability to scale cost-effectively. The data structures used e.g. key-value, wide column, graph, or document are different from default used in RDBMSs, making some operations faster and more flexible sometimes.The main reason not to use an SQL database is scalability, especially given the write-heavy workloads generated by modern web applications. For example:  An app like Facebook can’t be made to work on a straightforward SQL database, except by massive partitioning and slicing, which requires important adjustment to the application logic also, so Facebook developed Cassandra.Types of nosql databases model and their classification with examples:Wide-Column:This type of databases just like RDBMSs stores data in tables, but names and formats of columns can differ from row to row across the table. It groups related columns data collective.  E.g. Accumulo, Cassandra, Druid, HBase, Vertica.Document:This typically stores described BSON, JSON and XML documents. E.g. Apache CouchDB, ArangoDB, BaseX, Clusterpoint, Couchbase, Cosmos DB, IBM Domino, MarkLogic, MongoDB, OrientDB, Qizx, RethinkDBKey-value: This type provides importance to simplicity and useful in speedily allowing an application to support faster read and write processing of non-transactional data. e.g. Aerospike, Apache Ignite, ArangoDB, Couchbase, Dynamo, FairCom c-treeACE, FoundationDB, InfinityDB, MemcacheDB, MUMPS, Oracle NoSQL Database, OrientDB, Redis, Riak, Berkeley DB, SDBM/Flat File dbmGraph: This type of databases uses graph structures to query, store and map, relationships. It allows adjacent elements to linked together without using an index. E.g. AllegroGraph, ArangoDB, InfiniteGraph, Apache Giraph, MarkLogic, Neo4J, OrientDB, VirtuosoMulti-model: They accumulate some combination of the above described and support a broad number of applications. E.g. Apache Ignite, FoundationDB, ArangoDB, Couchbase, MarkLogic, InfinityDB, OrientDBKey benefits:NoSQL are column oriented databases. It seems to work better on both non-related and non-structured data. NoSQL databases give up some features of the traditional databases for speed and horizontal scalability.NoSQL databases are perceived to be safer, faster and cheaper to extend an existing program instead of getting it done from scratch.Today’s applications are expected to run non-stop and must efficiently manage continuously growing amounts of multi structured data in order to do so. This has caused NoSQL to grow from something to a serious consideration for every database from small to the big enterprise.