Graph Database Reliability

Offerings of Open Native Graph Database

Choosing a native graph database provides granular control over all operations from the transactional behavior to on-disk data organization to clustering and driver protocols. With complete control over every aspect of the native graph database, fine-tune graph traversal optimizations can be performed and choices sympathetic to graph principals for reliability and ACID transactional support can be made and implemented without restriction.

Durability and certainty of the graph database records are crucial to preserve. Choosing reliability and making sure failed graph database transactions roll back maintains a consistent data state in the native graph database.

For graph databases, reliability is far more essential than availability since the connectedness of the data make them more highly demanding than aggregate databases. The issue of placing a graph later over an existing datastore will boil down to how data is written and which record is factual since within a graph there are two perspectives: the node from each side.

If mutations are made through multiple requests simultaneously, it’ll lead to an uncertain relationship status. A non-native graph database will resolve this by means of complex algorithms, but in the end, they simply don’t work, leaving you with erroneous data. Such incorrectness can spread through the graph as well as other parts of your application that depend on relationships from a certain node perspective. If data correctness is your priority first and foremost, then it’s recommended to go for a native graph database like ONgDB.

ONgDB is a great example of a native graph database that offers reliability, transactional and modeling benefits along with high availability clustering, which are keys to creating reliable real-world systems today. To summarize:

• ONgDB is considered to be the most equipped free open source graph database in the world to date. Its production has been consistent since its inception in 2003. It remains open-source and has a huge following. Its development team is constantly interacting with the community so newly-introduced features and bugs can be fixed quickly.
• Geequel, while being strikingly similar to SQL is some instances, is the de-facto declarative query language created from the ground-up to query the graph database. The Java API can be utilized on JVM-sourced languages for high performance graph traversal. Since the availability of ONgDB is an open source it provides visibility into the thriving ecosystem building the necessary tools to surround its core database.
• The reliability of ONgDB is one of the many reasons why it’s being used in production by some of today’s leading companies. These include Cisco, Walmart, eBay, UBS, and countless others.
• The ONgDB graph database provides high availability clustering in ONgDB for production deployments.

We’ve experienced the benefits of choosing ONgDB as our fully open source, native graph database with each new release bringing more improvements and optimizations from top to bottom because of having complete control over the graph database stack. Get started quickly with ONgDB in GraphGrid Cloud.