Difference between MongoDB, CouchDB and MySQL

MongoDB is most popular database now days in software and web development. MongoDB (from “humongous”) is a scalable, high-performance, open source NoSQL database. This is Written in C++ languages.In this tutorial we will discuss features of mongoDB comparison between MongoDB vs CouchDB and MySQL.

Main featured of mongo db

Document-oriented

• Documents (objects) map nicely to programming language data types
• Embedded documents and arrays reduce need for joins
• Dynamically-typed (schemaless) for easy schema evolution
• No joins and no multi-document transactions for high performance and easy scalability

High performance

• No joins and embedding makes reads and writes fast
• Indexes including indexing of keys from embedded documents and arrays
• Optional streaming writes (no acknowledgements)

High availability

• Replicated servers with automatic master failover

Easy scalability

• Automatic sharding (auto-partitioning of data across servers)
• Reads and writes are distributed over shards
• No joins or multi-document transactions make distributed queries easy and fast
• Eventually-consistent reads can be distributed over replicated servers

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  MongoDB vs CouchDB vs MySQL Comparison Chart

  Difference between MongoDB vs CouchDB vs MySQL

  	CouchDB	MongoDB	MySQL
  Data Model	Document-Oriented ( JSON)	Document-Oriented BSON)	Relational
  Data Types	string,number,boolean,array,object	string, int, double, boolean, date, bytearray, object, array, others	link
  Large Objects (Files)	Yes (attachments)	Yes (GridFS)	Blobs
  Horizontal partitioning scheme	CouchDB Lounge	Auto-sharding	Partitioning
  Replication	Master-master (with developer supplied conflict resolution)	Master-slave and replica sets	Master-slave, multi-master, and circular replication
  Object(row) Storage	One large repository	Collection-based	Table-based
  Query Method	Map/reduce of javascript functions to lazily build an index per query	Dynamic; object-based query language	Dynamic; SQL
  Secondary Indexes	Yes	Yes	Yes
  Atomicity	Single document	Single document	Yes – advanced
  Interface	REST	Native drivers; REST add-on	Native drivers
  Server-side batch data manipulation	?	Map/Reduce, server-side javascript	Yes (SQL)
  Written in	Erlang	C++	C++
  Concurrency Control	MVCC	Update in Place
  Geospatial Indexes	GeoCouch	Yes	Spatial extensions
  Distributed Consistency Model	Eventually consistent (master-master replication with versioning and version reconciliation)	Strong consistency.  Eventually consistent reads from secondaries are available.	Strong consistency.  Eventually consistent reads from secondaries are available.