SPARQL (pronounced "sparkle" ˈspɑːkəl, a recursive acronym for SPARQL Protocol and RDF Query Language) is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format. It was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is recognized as one of the key technologies of the semantic web. On 15 January 2008, SPARQL 1.0 was acknowledged by W3C as an official recommendation, and SPARQL 1.1 in March, 2013. SPARQL allows for a query to consist of triple patterns, conjunctions, disjunctions, and optional patterns. Implementations for multiple programming languages exist. There exist tools that allow one to connect and semi-automatically construct a SPARQL query for a SPARQL endpoint, for example ViziQuer. In addition, tools exist to translate SPARQL queries to other query languages, for example to SQL and to XQuery. SPARQL allows users to write queries against what can loosely be called "key-value" data or, more specifically, data that follow the RDF specification of the W3C. Thus, the entire database is a set of "subject-predicate-object" triples. This is analogous to some NoSQL databases' usage of the term "document-key-value", such as MongoDB. In SQL relational database terms, RDF data can also be considered a table with three columns – the subject column, the predicate column, and the object column. The subject in RDF is analogous to an entity in a SQL database, where the data elements (or fields) for a given business object are placed in multiple columns, sometimes spread across more than one table, and identified by a unique key. In RDF, those fields are instead represented as separate predicate/object rows sharing the same subject, often the same unique key, with the predicate being analogous to the column name and the object the actual data. Unlike relational databases, the object column is heterogeneous: the per-cell data type is usually implied (or specified in the ontology) by the predicate value.

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Related concepts (16)
Triplestore
A triplestore or RDF store is a purpose-built database for the storage and retrieval of triples through semantic queries. A triple is a data entity composed of subject–predicate–object, like "Bob is 35" or "Bob knows Fred". Much like a relational database, information in a triplestore is stored and retrieved via a query language. Unlike a relational database, a triplestore is optimized for the storage and retrieval of triples. In addition to queries, triples can usually be imported and exported using Resource Description Framework (RDF) and other formats.
Document-oriented database
A document-oriented database, or document store, is a computer program and data storage system 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 NoSQL databases, and the popularity of the term "document-oriented database" has grown with the use of the term NoSQL itself. XML databases are a subclass of document-oriented databases that are optimized to work with XML documents.
NoSQL
A NoSQL (originally referring to "non-SQL" or "non-relational") database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Such databases have existed since the late 1960s, but the name "NoSQL" was only coined in the early 21st century, triggered by the needs of Web 2.0 companies. NoSQL databases are increasingly used in big data and real-time web applications.
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