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Amazon DocumentDB is a managed proprietary NoSQL database service that supports document data structures, with some compatibility with MongoDB version 3.6 (released by MongoDB in 2017) and version 4.0 (released by MongoDB in 2018). As a document database, Amazon DocumentDB can store, query, and index JSON data. It is available on Amazon Web ...
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):
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. MongoDB is developed by MongoDB Inc. and current versions are licensed under the Server Side Public License (SSPL). MongoDB is a member of the MACH Alliance.
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 ...
Internally, Cosmos DB stores "items" in "containers", [3] with these two concepts being surfaced differently depending on the API used (these would be "documents" in "collections" when using the MongoDB-compatible API, for example). Containers are grouped in "databases", which are analogous to namespaces above containers.
Pages in category "Table tennis" The following 11 pages are in this category, out of 11 total. This list may not reflect recent changes. ...
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]
Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.