Graph database growth curve spurred on with release of Neo4j 2.1
Graph database pioneers Neo Technology shook up the traditional RDMS world in 2000 with the launch of their radically different data management system. Following a decade or so of relatively conservative tinkering, the shock-meisters were at it again in December, with a shake-up of their core data model in Neo4j 2.0 (full summary of all the ace new additions here). Although their release of Neo4j 2.1 this week lacks any similarly dramatic changes, it has had a good number of tunings geared at upping productivity and performance.
With this latest drop, Neo4j now has an integrated ETL process (which stands for “Extract, Transform, Load”), which enables seamless data importing from relational and other data sources. The process makes it possible to combine data from differently structured data sources into a single target database.
Neo Technologies co-founder Emil Eifrem commented that: “Neo4j 2.1 represents a step forward in lowering the bar to graph database adoption for organizations who have massive amounts of data in their relational databases,” adding that “Companies are recognizing the value that comes from reimagining their existing data as a graph. The new built-in ETL capabilities here enable when moving data from an RDBMS into a graph.”