Integrating Graphs Into Your Existing Database

Tried and tested relational databases such as Oracle are trusted by enterprises for a reason. When we talk about making the shift to a graph database, we aren’t discounting the benefits that RDBMS provides for organisations in storing their highly structured and organised data. Sometimes, the reluctance lies in having to rip out a system that has money and time invested into it. 

But who says that to leverage the capabilities of graphs, you would have to replace your RDBMS database completely? The beauty of Neo4j is that it can co-exist with Oracle RDBMS, giving you the best of both worlds. I know what you’re thinking. Why should you fix a system that’s not broken? The answer is to get ahead. As discussed in the three previous blogs, connected data is precious in this data-driven age. 

With that said, by employing Neo4j and Oracle alongside one another, organisations benefit greatly from the availability of well-established technology and the strategic capabilities of a graph database. Your business can even improve application performance by offloading queries that leverage connected data, saving you time. When you break it down, relational databases and graph databases excel at different things. By having both capabilities in your arsenal, your organisation is agile enough to handle both structured and unstructured data.

Now comes the question of how? Neo4j has illustrated three different approaches to leveraging the power of a graph database:

Migrate or Sync a Subset of the Data Into Neo4j

By migrating, you take a portion of your data that is highly reliant on connections and store it on Neo4j so the application can ask for relationship information from Neo4j and consequently get details from the Oracle RDBMS database. This is done by exporting tables out of Oracle into Neo4j using CSV files. On the other hand, syncing uses middleware to synchronise a portion of data from the relational database to the graph database and can be done in real-time. 

Fully Sync Oracle and Neo4j Data

This approach takes the one previously mentioned a step further. Instead of synchronising a portion of the data, full synchronisation is used for applications that integrate data from multiple sources. It also helps in situations where the replacement of applications proves too high a cost. 

Migrate all Data Into Neo4j

The third approach is not so much getting both databases to co-exist in the same realm but entails the very thing that enterprises may not want to do. Sometimes there is just no saving the old ways, and organisations have to resort to ripping and replacing their RDBMS with a graph database. 

These approaches should be evaluated on a case-by-case basis for organisations depending on the needs of their enterprise applications. The first step to adopting new technology should be a thorough evaluation of organisational wants and needs. 

What are you waiting for? Start leveraging the power of your data today with both a relational and graph database by your side with Neo4j. Learn more about the coexistence of two database types in this informative whitepaper

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