comparison CouchDB vs MySQL Archives

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 Checkout other Recommended Tutorials, Top 6 RESTful API Frameworks for PHP 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.

comparison CouchDB vs MySQL

Difference between MongoDB, CouchDB and MySQL

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