Brief introduction of design features of MongoDB

MongoDB is a high-performance, open source, modeless document database designed to deliver high performance, horizontal scalability, high availability, and advanced accessibility, providing scalable, high-performance data storage solutions for Web applications. MongoDB's name is taken from the word "humogous" in the middle of a few characters, is very large, huge meaning. The database, developed by 10gen and provides technical support, is part of the NoSQL database family and can be used to replace traditional optical or key/value storage in many scenarios.
MongoDB uses C + + development implementation, does not support SQL, but has a powerful query syntax, its syntax is similar to object-oriented query language, can almost achieve similar relational database table query most of the functions.
MongoDB uses Bson (Binary JSON) as a unit of data storage and transmission. Bson is a JSON-like binary serialization document that supports nested objects and arrays. MongoDB is very much like relational database MySQL, documents (document) corresponds to the MySQL row (row), the collection (Collection) corresponds to the table in MySQL. MongoDB can run on a variety of operating system platforms such as Windows, Linux, OS X, and Solaris, and deployment is simpler.
MongoDB's design goals are high-performance, scalable, easy to deploy, easy to use, and easy to store data. Its main functional characteristics are as follows:
(1) For collection storage, it is easy to store data of object type. In MongoDB, data is grouped together in a collection that resembles a table in an RDBMS, and a collection can store an unlimited number of documents.
(2) Mode free, using the mode-free structure storage. In the collection of MongoDB, a schema-free document is stored, and using the modeless storage data is an important feature of the collection (Collection) that distinguishes the table (tables) from the RDBMS.
(3) Supports full indexing, which can be indexed on any property, including internal objects. MongoDB indexes are basically the same as the index of an RDBMS, which allows you to create indexes on the specified properties and internal objects to increase the speed of the query. In addition, MongoDB can provide the ability to create geospatial-based indexes.
(4) Support query. MongoDB supports rich query operations, and MongoDB almost supports most queries in SQL.
(5) Powerful aggregation tools. In addition to providing rich query functionality, MONGODB provides powerful aggregation tools such as count, group, and so on to support the use of MapReduce to complete complex aggregation tasks.
(6) Support for replication and data recovery. MongoDB supports the master-slave replication mechanism, which can realize data backup, fault recovery, read extension and so on. The replication mechanism based on replica set provides the function of automatic fault recovery, ensuring that the cluster data is not lost.
(7) Use efficient binary data storage, including large objects such as video. With binary format storage, you can save any type of data object.
(8) Automatic processing of fragmentation to support the expansion of the cloud level. MONGODB support cluster automatic segmentation data, fragmentation of the data can enable the cluster to store more data, to achieve greater load, but also to ensure that the storage load balance.
(9) Support for Perl, PHP, Java, C #, JavaScript, Ruby, C and C + + language drivers, Mon provides a current database-driven package for all major development languages, and developers can easily program with any major development language Implements access to the MongoDB database.
(10) The file storage format is Bson (an extension of JSON). Bson is the abbreviation for binary format JSON, Bson supports the nesting of documents and arrays.
(11) The MongoDB database can be accessed remotely through the network.