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MongoDB is a source-available, cross-platform, document-oriented database program. Classified as a NoSQL database product, MongoDB utilizes 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).
JSON or JavaScript Object Notation, is an open standard format that uses human-readable text to transmit data objects. JSON has been popularized by web services developed utilizing REST principles. Databases such as MongoDB and Couchbase store data natively in JSON format, leveraging the pros of semi-structured data architecture.
A document-oriented database is a specialized key-value store, which itself is another NoSQL database category. In a simple key-value store, the document content is opaque. A document-oriented database provides APIs or a query/update language that exposes the ability to query or update based on the internal structure in the document. This ...
Documents are addressed in the database via a unique key that represents that document. Another defining characteristic of a document-oriented database is an API or query language to retrieve documents based on their contents. Different implementations offer different ways of organizing and/or grouping documents: Collections; Tags; Non-visible ...
The equivalent of ORMs for document-oriented databases are called object-document mappers (ODMs). Document-oriented databases also prevent the user from having to "shred" objects into table rows. Many of these systems also support the XQuery query language to retrieve datasets. Object-oriented databases tend to be used in complex, niche ...
A database object is a structure for storing, managing and presenting application- or user-specific data in a database. Depending on the database management system (DBMS), many different types of database objects can exist. [1] [2] The following is a list of the most common types of database objects found in most relational databases (RDBMS):
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Compared to JSON, BSON is designed to be efficient both in storage space and scan-speed. Large elements in a BSON document are prefixed with a length field to facilitate scanning. In some cases, BSON will use more space than JSON due to the length prefixes and explicit array indices. [2]