Couchbase

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Relational Database Management Systems (RDBMS).

RDBMS is adatabase management system, which is based on the relational model invented by E. F. Codd, that has features such as normalization, joins, foreign keys, and so on. (Examples of such a database management system would be MySQL, Oracle, DB2 DB, and so on). RDBMS provides features such as transactions, table joins, locking mechanisms, ACID properties, and so on. However, there are some limitations to RDBMS, predominantly in terms of scalability and readiness for schema changes.

NOTE

ACID stands for Atomicity, Consistency, Isolation, and Durablity. These are properties that are essential for supporting transactions in any database system. In order to guarantee a meaningful and successful transaction, the system has to support all of these properties:

Atomicity: The operation will be performed as a single unit

Consistency: All the operations will ensure a valid state and consistency of data at the end of the transaction

Isolation: No two transactions will intervene with each other

Durability: The transaction will survive system failures

vertical scaling, wherein you increase the hardware resources in terms of CPU and RAM.

Horizontal scaling, wherein you increase the sever nodes.

If we need to scale database servers horizontally, we need to find a mechanism to distribute data across the servers, balance the load, and what not! The only easy way left is to increase your hardware resources. However, after a certain stage, physical servers can't expand further due to limitations of sockets, chips, and so on, just like if you have four CPU socket servers, then you cannot scale up further than that. Therefore, we need to find a way to scale out, horizontally.

Due to dynamics in business functions, the database schema needs to be changed very frequently, which is very common in agile development. It is difficult to incorporate the changes in RDBMS. Sometimes you need to bring the application down to modify the schema, such as adding one column in a table. In order to address such issues, companies such as Facebook and Google started exploring alternatives to RDBMS for data storage that can scale out and handle changes in schemas seamlessly without any impact on business operations. These are the fundamentals of NoSQL.

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So what is NoSQL?

NoSQL is a nonrelational database management system.

It is designed for distributed data stores in which there are very large-scale data storage requirements (terabytes and petabytes of data).

not require fixed schemas, avoid join operations, and typically scale horizontally

categories of NoSQL

Key-value store: A simple data storage system that uses a key to access values. Some examples are Redis, Riak, and DynamoDB.

Use Case: Multiplayer online gaming to manage each player session.

Column family store: A sparse matrix system that uses a row and a column as keys, for example, Apache HBase, Apache Cassandra.

Use Case: Stream massive write loads such as log analysis.

Graph store: This is used for relationship-intensive problems. An example is Neo4j.

Use Case: Complicated graph problems, such as moving from one point to another.

Document store: This is used to store hierarchical data structures directly in the database, for example, MongoDB (10Gen), CouchDB, and Couchbase.

Use Case: Storing structured product information.

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