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Introducing Open Native Graph Database into Your Graph Data Architecture

Graph Database Data Model Flexibility

Enterprise Data Challenge

Inserting Open Native Graph Database

Introducing Open Native Graph Database into your graph data architecture using GraphGrid Connected Data PlatformA graph database is capable of offering long-lasting competitive advantages for organizations worldwide from startups to the largest enterprise. Interest within the enterprise sector surged dramatically the past two years and Forrester recently projected that graph databases will reach over 80% of leading enterprises within two years. Graph databases provide business benefits because graph databases make use of intuitive principles of the connections experienced between everything and everyone as a realistic representation of the way the world interacts. Even with all the benefits discussed in Graph Advantage: Why Every Enterprise Should Use a Graph Database, the introduction of a graph data architecture into an enterprise, especially one that may have just finished getting their Hadoop implementation into production, can seem risky.

One of the great strengths of a the Open Native Graph Database (ONgDB) is it’s schema free flexible data model, which it turns out provides a very low-risk entry point as way for an enterprise to begin to explore the benefits of using a graph database. The Open Native Graph Database is made to model and navigate connected data with high performance. The Open Native Graph Database processes and stores data within the node and relationship structure defined by the written data, making it flexible enough to accommodate the many data models of the existing databases within an enterprise.

We know it’s not reasonable for an enterprise to go all in on a graph and try to replace existing SQL or NoSQL databases overnight and certainly a Hadoop data lake isn’t going to be replaced by a graph database. This is because the number of applications requiring migration across the organization would be insurmountable. A majority of transactional data stores made to gather data from clicks, sensors, and others around us will keep existing in the enterprise since they’re capable of managing data streams at the microsecond level.

So what does this path forward look like?

While a graph is capable of replacing certain SQL and NoSQL stores to power real-time applications for recommendations, analytics, connected customer views, etc., the path to begin benefitting from a graph database such as ONgDB is a lot shorter than you think. ONgDB plugs in efficiently alongside current databases in any enterprise thanks to the efficient data import capabilities that can be utilized to connect and flow data into ONgDB continuously — a tooling and an advantage seen in the GraphGrid Connected Data Platform. This pushes an enterprise to start connecting data and leveraging it after only a few weeks to take advantage of the graph data architecture.

When an enterprise becomes confident in managing data flow and it experiences the benefits of connecting data previously soiled by department, other data stores may likely be retired as the enterprise migrates all new systems and applications to the use the Open Native Graph Database as the source of truth enabling the transition to a connected enterprise.