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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    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, otherslink
    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.