By Aileen Agricola | May 27, 2014
Adoption [of version 2.0] has grown so explosively that the entire graph database category has grown significantly faster than any database category in popularity – Philip Rathle, vice president of products, Neo TechnologyInterest in graph databases has exploded during the first five months of the year, as the product category threatens to lap other database types in popularity, according to figures from DB-Engines.com. The surge is a natural response to people’s desire for an easy and intuitive way to find connections hidden in data, says graph database leader Neo Technology, which is rolling out version 2.1 of Neo4j this week. Up until December, interest in graph databases closely matched the interest in NoSQL databases, including wide column stores, document stores, RDF stores, key-value stores, and others. (Graph databases are now considered a separate category from NoSQL databases, but that’s another story.) Interest in all of these database categories has been growing steadily for a while, as people seek technologies that can help solve big (and pesky mid-size) data-related challenges.graph database popularity But in January, people’s interests changed quite dramatically, and the graph database category shot out far ahead of its NoSQL compatriots, according to DB-Engines, which uses various sources of data to rank databases and track database adoption trends, including Web searches, discussions in public forums, and job offers, among others. It’s hard to tell what caused the sudden interest in graph databases. It could be that people suddenly realized relational databases can’t do what they need them to and decided to give graph a try. It could be that organizations felt a sudden and intense desire to emulate the technology that power the social media empires of Facebook and LinkedIn. Or it could be that the Seattle Seahawks won the Super Bowl. In big data, when faced with a multitude of facts, it’s tempting to downshift from causation to correlation. Read the full article.
Keywords: DB Engines