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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 ...
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 ...
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).
Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
MongoDB uses JSON-like data for its document-oriented database. Some relational databases, such as PostgreSQL and MySQL, have added support for native JSON data types. This allows developers to store JSON data directly in a relational database without having to convert it to another data format.
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]
The inverse document frequency is a measure of how much information the word provides, i.e., how common or rare it is across all documents. It is the logarithmically scaled inverse fraction of the documents that contain the word (obtained by dividing the total number of documents by the number of documents containing the term, and then taking ...