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MongoDB is a source-available, cross-platform, document-oriented database program. Classified as a NoSQL database product, MongoDB uses JSON-like documents with optional schemas. Released in February 2009 by 10gen (now MongoDB Inc.), it supports features like sharding, replication, and ACID transactions (from version 4.0).
The central concept of a document-oriented database is the notion of a document.While each document-oriented database implementation differs on the details of this definition, in general, they all assume documents encapsulate and encode data (or information) in some standard format or encoding.
The name "BSON" is based on the term JSON and stands for "Binary JSON". [2] It is a binary form for representing simple or complex data structures including associative arrays (also known as name-value pairs), integer indexed arrays, and a suite of fundamental scalar types. BSON originated in 2009 at MongoDB. Several scalar data types are of ...
While JSON provides a syntactic framework for data interchange, unambiguous data interchange also requires agreement between producer and consumer on the semantics of specific use of the JSON syntax. [25] One example of where such an agreement is necessary is the serialization of data types that are not part of the JSON standard, for example ...
Examples: MongoDB, Cassandra, ScyllaDB, CouchDB, Redis. Document stores: Document stores store data in a semi-structured format, typically using JSON or XML documents. Each document can have a different structure, providing flexibility. Examples: MongoDB, CouchDB. Key-value stores: Key-value stores store data as pairs of keys and values.
MongoDB, Inc. is an American software company that develops and provides commercial support for the source-available database engine MongoDB, a NoSQL database that stores data in JSON-like documents with flexible schemas. MongoDB, Inc. is a member of the MACH Alliance. [2]
Note (2): Materialized views are not supported in Informix; the term is used in IBM's documentation to refer to a temporary table created to run the view's query when it is too complex, but one cannot for example define the way it is refreshed or build an index on it. The term is defined in the Informix Performance Guide.
With document databases like MongoDB it is common to put more data in a smaller number of collections. For example, in a blogging application, one might choose to store comments within the blog post document, so that with a single retrieval one gets all the comments.