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. |
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