by Angela Guess

A press release out of Bitnine reports, “Volume, Velocity, Variety, Veracity, Variability. The conventional Relational DBMS, the majority of the current DBMS market, has critical limitations in handling these 5Vs of Big Data. No matter how the existing DBMS vendors have improved the capability of the current DBMS’s, they have ended up finding that they cannot catch up with the rapid advances since the data environment is a moving target. Data is no longer small, simple, static, but big, complex and dynamic. In this sense of urgency, Graph Database is created to hover beyond the limit of the current DMBS’s. Graph Database is rapidly expanding its market share (CAGR of 40%) in the DBMS industry, even though relatively few corporates have implemented the technology to solve specific problems. Forrester Research analysts recently reported that graph databases — the fastest growing category in database management systems — will reach more than a quarter of enterprises by 2017.”

The release goes on, “This world is hyper-connected now. There is no completely isolated information. A graph database uses semantic queries with nodes, edges, and properties to represent data. The relationships allow data in the store to be linked together at once, and in most cases retrieved with an undivided operation. This contrasts with conventional relational databases, where links between data are stored in the data itself and are gathered by searching for this data within the store and using the JOIN concept to collect the related data. Graph databases are designed to allow simple and rapid retrieval of complex hierarchical structures that are difficult to model in relational systems. Furthermore, the speed execution is not degraded as the data set volume increases, unlike the existing databases.”

Read more at Business Wire.

Photo credit: Bitnine