|This article relies on references to primary sources. (May 2012)|
A document-oriented database is a computer program designed for storing, retrieving, and managing document-oriented information, also known as semi-structured data. Document-oriented databases are one of the main categories of so-called NoSQL databases and the popularity of the term "document-oriented database" (or "document store") has grown with the use of the term NoSQL itself. In contrast to well-known relational databases and their notions of "Relations" (or "Tables"), these systems are designed around an abstract notion of a "Document".
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 formats or encodings. Encodings in use include XML, YAML, JSON, and BSON, as well as binary forms like PDF and Microsoft Office documents (MS Word, Excel, and so on).
Documents inside a document-oriented database are similar, in some ways, to records or rows in relational databases, but they are less rigid. They are not required to adhere to a standard schema, nor will they have all the same sections, slots, parts, or keys. For example, the following is a document:
Address:"5 Oak St.",
A second document might be:
Address:"15 Wanamassa Point Road",
These two documents share some structural elements with one another, but each also has unique elements. Unlike a relational database where every record contains the same fields, leaving unused fields empty; there are no empty 'fields' in either document (record) in the above example. This approach allows new information to be added to some records without requiring that every other record in the database shares the same structure.
Documents are addressed in the database via a unique key that represents that document. This key is often a simple string, a URI, or a path. The key can be used to retrieve the document from the database. Typically, the database retains an index on the key to speed up document retrieval.
Another defining characteristic of a document-oriented database is that, beyond the simple key-document (or key-value) lookup that can be used to retrieve a document, the database offers an API or query language that allows the user to retrieve documents based on their content. For example, you may want a query that retrieves all the documents with a certain field set to a certain value. The set of query APIs or query language features available, as well as the expected performance of the queries, varies significantly from one implementation to the next.
Implementations offer a variety of ways of organizing documents, including notions of
- Non-visible Metadata
- Directory hierarchies
|BaseX||BaseX Team||BSD License||Java, XQuery||Support for XML, JSON and binary formats; client-/server based architecture; concurrent structural and full-text searches and updates; REST APIs.||Yes|
|Cloudant||Cloudant, Inc.||Proprietary||Erlang, Java, Scala, and C||Distributed database service based on BigCouch, the company's open source fork of the Apache-backed CouchDB project.||Yes|
|Clusterpoint||Clusterpoint Ltd.||Free community license / Commercial||C++||Schema-free, document-oriented database management system platform with server based data storage, full text search engine functionality, information ranking for search relevance and clustering.||Yes|
|Couchbase Server||Couchbase, Inc.||Apache License||Erlang and C||Distributed NoSQL Document Database.||Yes |
|CouchDB||Apache Software Foundation||Apache License||Erlang||JSON over REST/HTTP with Multi-Version Concurrency Control and limited ACID properties. Uses map and reduce for views and queries.||Yes |
|eXist||eXist, ||GPL||XQuery, Java||XML over REST/HTTP, WebDAV, Lucene Fulltext search, validation, versioning, clustering, triggers, URL rewriting, collections, ACLS, XQuery Update||Yes |
|FleetDB||FleetDB||MIT License||Clojure||A JSON-based schema-free database optimized for agile development.||(unknown)|
|Jackrabbit||Apache Software Foundation||Apache License||Java||(unknown)|
|Lotus Notes||IBM||Proprietary||LotusScript, Java, Lotus @Formula||(unknown)|
|MarkLogic||MarkLogic Corporation||Free Express license or Commercial||REST, Java, XQuery, XSLT, C++||Distributed document-oriented database with Multi-Version Concurrency Control, integrated Full text search and ACID-compliant transaction semantics||Yes|
|MongoDB||10gen, Inc||GNU AGPL v3.0||C++||Document-oriented database optimized for highly transient data||Optional |
|MUMPS Database||Proprietary and GNU Affero GPL||MUMPS||Commonly used in health applications.||(unknown)|
|OrientDB||Orient Technologies||Apache License||Java||JSON over HTTP||Yes|
|Apache Cassandra||Apache Software Foundation||Apache License||Java||JSON over HTTP||Yes|
|Redis||BSD License||ANSI C||Key-value store supporting lists and sets with binary-safe protocol||(unknown)|
|Rocket U2||Rocket Software||Proprietary||UniData, UniVerse||Yes (Beta)|
XML database implementations 
Most XML databases are document-oriented databases.
See also 
- Internet Message Access Protocol (IMAP)
- Database theory
- In-memory database
- Object database
- Online database
- Real time database
- Relational database
- Data hierarchy
Further reading 
- Assaf Arkin. (2007, September 20). Read Consistency: Dumb Databases, Smart Services. Labnotes:Don’t let the bubble go to your head!