NoSQL

In computing, NoSQL (commonly interpreted as "not only SQL") is a broad class of database management systems identified by non-adherence to the widely used relational database management system model. NoSQL databases are not built primarily on tables, and generally do not use SQL for data manipulation.

NoSQL database systems are often highly optimized for retrieval and appending operations and often offer little functionality beyond record storage (e.g. key–value stores). The reduced run-time flexibility compared to full SQL systems is compensated by marked gains in scalability and performance for certain data models.

In short, NoSQL database management systems are useful when working with a huge quantity of data when the data's nature does not require a relational model. The data can be structured, but NoSQL is used when what really matters is the ability to store and retrieve great quantities of data, not the relationships between the elements. Usage examples might be to store millions of key–value pairs in one or a few associative arrays or to store millions of data records. This organization is particularly useful for statistical or real-time analyses of growing lists of elements (such as Twitter posts or the Internet server logs from a large group of users).

Characteristics

NoSQL databases have a number of distinctive characteristics relative to traditional SQL-based relational databases.^{[citation needed]}

NoSQL does not use SQL as its query language. NoSQL database systems arose alongside major Internet companies, such as Google, Amazon, and Facebook, which had challenges in dealing with huge quantities of data with which conventional RDBMS solutions could not cope. Note that both the Facebook and Twitter infrastructures are largely based on MySQL databases. NoSQL database systems are developed to manage large volumes of data that do not necessarily follow a fixed schema. Data is partitioned among different machines (for performance reasons and size limitations) so that traditional JOIN operations cannot be used.^{[citation needed]}

NoSQL cannot necessarily give full ACID guarantees. Usually only eventual consistency is guaranteed or transactions limited to single data items. This means that given a sufficiently long period of time over which no changes are sent, all updates can be expected to propagate eventually through the system.^{[citation needed]}

NoSQL has a distributed, fault-tolerant architecture. Several NoSQL systems employ a distributed architecture, with the data held in a redundant manner on several servers. In this way, the system can easily scale out by adding more servers, and failure of a server can be tolerated. This type of database typically scales horizontally and is used for managing large amounts of data, when the performance and real-time nature is more important than consistency (as in indexing a large number of documents, serving pages on high-traffic web sites, and delivering streaming media).^{[citation needed]}

History

Carlo Strozzi used the term NoSQL in 1998 to name his lightweight, open-source relational database that did not expose the standard SQL interface. Strozzi suggests that, as the current NoSQL movement "departs from the relational model altogether; it should therefore have been called more appropriately 'NoREL'.

Eric Evans, a Rackspace employee, reintroduced the term NoSQL in early 2009 when Johan Oskarsson of Last.fm wanted to organize an event to discuss open-source distributed databases. The name attempted to label the emergence of a growing number of non-relational, distributed data stores that often did not attempt to provide atomicity, consistency, isolation and durability guarantees that are key attributes of classic relational database systems.

In 2011, work began on UnQL (Unstructured Query Language), a specification for a query language for NoSQL databases. Like XQuery it is designed to query collections (versus tables) of documents (versus rows) with loosely defined fields (versus columns). UnQL is claimed to be a superset of SQL within which SQL is a very constrained type of UnQL for which the queries always return the same fields (same number, names and types). However, UnQL does not cover the data definition language (DDL) SQL statements like CREATE TABLE or CREATE INDEX.

Taxonomy

See also: Comparison of structured storage software

Often, NoSQL databases are categorized according to the way they store the data and fall under categories such as key–value stores, BigTable implementations, document store databases, and graph databases. With the rise of the real-time web, there was a need to provide information out of large volumes of data which more or less followed similar horizontal structures. As such, NoSQL databases are often highly optimized for retrieve and append operations and often offer little functionality beyond record storage (e.g. key–value stores). The reduced run time flexibility compared to full SQL systems is compensated by large gains in scalability and performance for certain data models.^{[citation needed]}

NoSQL implementations can be categorized by their manner of implementation:

Document store

The central concept of a document store is the notion of a "document". While each document-oriented database implementation differs on the details of this definition, in general, they all assume that 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).

Different implementations offer different ways of organizing and/or grouping documents:

• Collections
• Tags
• Non-visible Metadata
• Directory hierarchies

Compared to relational databases, for example, collections could be considered as tables as well as documents could be considered as records. But they are different: every record in a table has the same sequence of fields, while documents in a collection may have fields that are completely different.

Documents are addressed in the database via a unique key that represents that document. One of the other defining characteristics of a document-oriented database is that, beyond the simple key-document (or key–value) lookup that you can use to retrieve a document, the database will offer an API or query language that will allow retrieval of documents based on their contents.

Main articles: Document-oriented database and XML database

Name	Language	Notes
ArangoDB	C, C++ & Javascript	Multi model JSON document store
BaseX	Java, XQuery	XML database
Clusterpoint	C++	geared for Full text search
Couchbase Server	Erlang, C++	Support for JSON and binary documents
Apache CouchDB	Erlang	JSON store
eXist	Java, XQuery	XML database
Jackrabbit	Java
Lotus Notes and IBM Lotus Domino	LotusScript, Java, IBM X Pages, others	MultiValue
MarkLogic Server	XQuery, Java, REST	XML database with support for JSON, text, and binaries
MongoDB	C++, C#	BSON store (binary format JSON)
OpenLink Virtuoso	C++, C#, Java, SPARQL	middleware and database engine hybrid
OrientDB	Java
Sedna	XQuery, C++	XML database
SimpleDB	Erlang
Oracle NoSQL Database	Java

Graph

This kind of database is designed for data whose relations are well represented as a graph (elements interconnected with an undetermined number of relations between them). The kind of data could be social relations, public transport links, road maps or network topologies, for example.

Main article: Graph database

Name	Language	Notes
AllegroGraph	SPARQL	RDF GraphStore
ArangoDB	C, C++ & Javascript	Multi model JSON document store with graph support
IBM DB2	SPARQL	RDF GraphStore added in DB2 10
DEX	Java, C++	High-performance Graph Database
FlockDB	Scala
InfiniteGraph	Java	High-performance, scalable, distributed Graph Database
Neo4j	Java
OpenLink Virtuoso	C++, C#, Java, SPARQL	middleware and database engine hybrid
OrientDB	Java
Pregel
Sones GraphDB	C#
OWLIM	Java, SPARQL 1.1	RDF graph store with reasoning

Key–value store

Key–value stores allow the application to store its data in a schema-less way. The data could be stored in a datatype of a programming language or an object. Because of this, there is no need for a fixed data model. The following types exist:

Eventually‐consistent key‐value store

• Apache Cassandra
• Dynamo
• Hibari
• OpenLink Virtuoso
• Project Voldemort
• Riak

Hierarchical key–value store

• GT.M
• InterSystems Caché

Hosted services

• Freebase
• OpenLink Virtuoso
• Datastore on Google Appengine
• Amazon DynamoDB
• Cloudant Data Layer (CouchDB)

Key–value cache in RAM

• memcached
• OpenLink Virtuoso
• Oracle Coherence
• Redis
• Hazelcast
• Tuple space
• Velocity

Key–value stores on solid state or rotating disk

• ArangoDB
• BigTable
• CDB
• Ceph
• Couchbase Server
• Keyspace
• LevelDB
• MemcacheDB
• MongoDB
• OpenLink Virtuoso
• Tarantool
• Tokyo Cabinet
• Tuple space
• Oracle NoSQL Database

Ordered key–value stores

• Berkeley DB
• IBM Informix C-ISAM
• InfinityDB
• MemcacheDB
• NDBM

Multivalue databases

• Northgate Information Solutions Reality, the original Pick/MV Database
• Extensible Storage Engine (ESE/NT)
• jBASE
• OpenQM
• Revelation Software's OpenInsight
• Rocket U2
• D3 Pick database
• InterSystems Caché
• InfinityDB

Object database

Main article: Object database

• db4o
• Eloquera
• GemStone/S
• InterSystems Caché
• JADE
• NeoDatis ODB
• ObjectDB
• Objectivity/DB
• ObjectStore
• OpenLink Virtuoso
• Versant Object Database
• Wakanda
• ZODB

RDF database

• Meronymy SPARQL Database Server

Tabular

• Apache Accumulo
• BigTable
• Apache Hbase
• Hypertable
• Mnesia
• OpenLink Virtuoso

Tuple store

• Apache River
• OpenLink Virtuoso
• Tarantool

See also

• CAP theorem
• Comparison of object database management systems
• Comparison of structured storage software
• Faceted search
• List of object database management systems
• Triplestore
• RDF Database
• Distributed cache

Further reading

• Pramod Sadalage and Martin Fowler (2012). NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Addison-Wesley. ISBN 0-321-82662-0.

External links

• NoSQL whitepaper
• NoSQL general introduction article