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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 ...
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 ...
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).
In computer programming, a collection is an abstract data type that is a grouping of items that can be used in a polymorphic way. Often, the items are of the same data type such as int or string . Sometimes the items derive from a common type; even deriving from the most general type of a programming language such as object or variant .
where N is the total number of documents in the collection, and () is the number of documents containing . There are several interpretations for IDF and slight variations on its formula. In the original BM25 derivation, the IDF component is derived from the Binary Independence Model .
Since the early 1990s, the operational database software market has been largely taken over by SQL engines. In 2014, the operational DBMS market (formerly OLTP) was evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases.
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]