Enterprises Move to Graph Databases

Enterprises Move to Graph Databases

Enterprises Move to Graph Databases

Graph databases continue to make their move into mainstream enterprise operations, providing a good reason for big name vendors to have planted their flags in the space and for one leader in the arena, Neo4j, to be enjoying strong growth among large business customers. As of January the vendor continues to hold the top spot in the category in the DB-Engines Ranking of database systems according to popularity.

In December, Bloor Research published an update on the graph database world, noting that Oracle and Teradata “are both examples of major companies that have implemented graph capabilities on top of existing relational technology.” It points out, as well, that companies including IBM and Informatica are using third-party graph technology in their products, while the market itself undergoes consolidation with acquisitions such as Aurelius, the developer of the Titan graph database, by DataStax.

“Despite all of this attention the market is dominated by Neo4J and OntoText (GraphDB), which are graph and RDF (or triplestore) database providers respectively,” analyst Philip Howard writes, explaining that the difference between a true graph product and a triplestore is that the former enables users to traverse a graph without needing an index and the latter doesn’t. “These are the longest established vendors in this space (both founded in 2000) so they have a longevity and experience that other suppliers cannot yet match,” Howard notes.

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Neo4j is clearly invested in keeping an upper hand:  VP of Global Marketing Utpal Bhatt points to its recent $36 million funding infusion as one event that will help it maintain its top spot. It plans to use the cash to expand both its engineering function to develop even more capabilities that take advantage of relationships that exist within data and also to further fund sales and marketing efforts. Both steps will be helpful as the company pursues what is already its fastest-growing customer segment, which Bhatt says are enterprises with more than $1 billion in revenue. Such clients now represent more than half of Neo4j’s customers.

Quite a change from 2015, when Neo4j CEO Emil Eifrem told DATAVERSITY® that time still needed to be spent on making,

“Sure the world understands how valuable it is to take existing applications and re-imagine them from a graph perspective to gain a big advantage, or build completely new products and services based on graphs.”

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Bhatt thinks it’s great that new players – and big players – are now part of the graph databases category. “It’s a strong endorsement of how the space is truly becoming mainstream and impactful,” he says, “and we’ve only scratched the surface.”

Increased competition comes along with the category endorsement, of course. Bhatt explains that many of the competing vendors that come from the traditional database world take a non-native approach to their graph database offerings. That is, they build a graph layer atop their relational database technology: While this has benefits for companies that want to work with a single database vendor as much as possible and is an appropriate option for lightweight graph use cases, he says, “It’s not well-suited for what we call core graph apps.”

For Neo4j, the graph is home turf, and as companies work with more and more connected data:

“The native approach will beat the non-native approach in terms of intuitiveness, performance – especially real-time performance – and the ability to meet changing requirements and new different data types without having to go through extensive schema changes,” he says.

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His take is that even companies where relational databases still rule will want to use a native graph database for certain use cases, “To meet the scale and performance requirements of applications that rely on highly connected data.” In the future, he expects enterprises to standardize on both relational and NoSQL stacks.



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