New Query Language for Graph Databases to Become International Standard


Neo4j Backs Launch of GQL Project: First New ISO Database Language Since SQL


SAN MATEO, Calif. – September 17, 2019  – Neo4j, the leader in graph databases, announced today that the international committees that develop the SQL standard have voted to initiate GQL (Graph Query Language) as a new database query language. Now to be codified as the international standard declarative query language for property graphs, GQL represents the culmination of years of effort by Neo4j and the broader database community.

Neo4j News: GQL to incorporate and consider several graph database languages

The initiative for GQL was first advanced in the GQL Manifesto in May 2018. A year later, the project was considered at an international gathering in June. Ten countries including the United States, Germany, UK, Korea, and China have now voted in favor, with seven countries promising active participation by national experts.

It has been well over 30 years since ISO/IEC began the SQL project. SQL went on to become the dominant language for accessing relational data, achieving wide adoption by vendors and practitioners and dramatically accelerating the growth of the relational database market. The GQL project will initiate development of the next generation of technology standards for accessing data, optimized for today’s world of connected data. Its charter mandates building on core foundations already established by SQL, as well as ongoing collaboration to ensure SQL and GQL compatibility and interoperability. 

Stefan Plantikow, Product Manager and Standards Engineer for Property Graph Querying at Neo4j, serves as a GQL project lead and editor of the planned GQL specification. He has many years of experience developing the Cypher language, a key source for GQL.

“I believe now is the perfect time for the industry to come together and define the next generation graph query language standard,” said Plantikow. “It’s great to receive formal recognition of the need for a standard language. Building upon a decade of experience with property graph querying, GQL will support native graph data types and structures, its own graph schema, a pattern-based approach to data querying, insertion and manipulation, and the ability to create new graphs, and graph views, as well as generate tabular and nested data. Our intent is to respect, evolve, and integrate key concepts from several existing languages including graph extensions to SQL.”

GQL reflects fast growth in the graph database market, demonstrated by increasing adoption of the Cypher language, which has shown potential and powered the demand for a single, standard language to play the role of SQL for graph databases. 

In addition to Neo4j, many companies are already taking part in GQL-related activities including Redis Labs, SAP and IBM. National experts from China, Korea are joining existing participants centred in Europe and the U.S. 

Keith Hare, who has been active in the SQL Standards process since 1988 and has served as the chair of the international SQL standards committee for database languages since 2005, charted the progress toward GQL. 

“We have reached a balance of initiating GQL, the database query language of the future whilst preserving the value and ubiquity of SQL,” said Hare. “Our committee has been heartened to see strong international community participation to usher in the GQL project.  Such support is the mark of an emerging de jure and de facto standard .”

For more information about graph query language standardization It’s Time for a Single Property Graph Query Language on the Neo4j blog.

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Neo4j is the leading graph database platform that drives innovation and competitive advantage at Airbus, Comcast, eBay, NASA, UBS, Walmart and more. Thousands of community deployments and more than 300 customers harness connected data with Neo4j to reveal how people, processes, locations and systems are interrelated. Using this relationships-first approach, applications built using Neo4j tackle connected data challenges including artificial intelligence, fraud detection, real-time recommendations and master data. Find out more at neo4j.com.      

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