A graph database is a data management system software. The building blocks are vertices and edges. To put it in a more familiar context, a relational database is also a data management software in which the building blocks are tables. Both require loading data into...
Originally featured on DZone Motivation GSQL is a Turing complete Graph Database query language. Compared to other graph query languages, the biggest advantage is its support of Accumulators — global or attachable to each vertex. In addition to providing the classic pattern match syntax, which is easy to master, GSQL supports...
In our upcoming 2.4 release, TigerGraph will offer a major syntax extension in GSQL - pattern matching. Pattern matching enables users to focus on specifying what multi-hop path pattern they want in a query block, without worrying about the direction of the underlying data flow....
Since the introduction of the TigerGraph Developer Edition in June 2018, the GSQL language has generated a lot of interest and a lot of valuable feedback. In general, the feedback has been positive for GSQL’s ease of use, high performance, and high expressive power. Here...
In May this year, Amazon announced the General Availability of its cloud graph database service called Amazon Neptune. Here is a comprehensive blog that summarizes its strengths and weaknesses. Last year, we published a benchmark report on Neo4j, Titan and TigerGraph. It is intriguing for...
Prelude In December, I wrote a Quora post on the pros and cons of graph databases. I shared two cons pervasive in the market today: the difficulty of finding proficient graph developers, and how non-standardization on a graph query language is slowing down enterprise adoption, especially...
