Neo4j

Fig 02 - Neo4j Bloom

Unusually for a property graph, SPARQL is supported. So too is Gremlin (part of the Apache Tinkerpop project). Perhaps more significantly, the company has introduced a “BI Connector” which translates SQL queries into Cypher, with an initial focus on supporting Tableau so that you can use this instead of, or alongside, Neo4j Bloom, where the latter provides a visualisation and communication interface for non-technical users so that they can explore, edit and search graphs, and create storyboards. This is illustrated in Figure 2.

Also, importantly, the company is a driving force behind GQL (graph query language), which is intended to be a common standard for graph databases. under the ageas of the ANSI standards committee. This initiative is supported by a range of technology vendors including Talend, SAP, Tableau and others.

Fig 03 - Graph algorithms provided by Neo4j

A significant recent release is the Neo4j Graph Data Science Library, which works in conjunction with Neo4j Bloom to support advanced analytics and machine learning. More than 50 graph algorithms (see Figure 3) are supported and have been optimised for robust scale and parallelised for performance. This last point is important because there are some vendors offering parallelised graph algorithms (consider MADlib for example) running against relational databases. And the problem there is that there are only a limited number of such algorithms can be parallelised in a relational environment, whereas Neo4j is able to offer a much comprehensive set of capabilities. Finally, in the context of analytic and query support, it is also worth noting that Neo4j supports 3D geospatial capabilities.

Neo4j is the clear market leader in the graph space. It has the most users, it uses and drives a widely adopted query language. In many respects, it has consistently been a lot more innovative than its competitors. This is in part because of the maturity of the product and partly because its success has meant that it has the resources to introduce such developments more quickly. Its competitors have historically argued that the product did not scale well but the multi-clustering and sharding that are now available should knock that argument on its head. Some vendors that specialise in analytics will claim that they can outperform Neo4j and this may be valid, but Neo4j does not have this limited focus: it is, in effect, the Oracle or SQL Server of the graph database world. It is not the equivalent of Teradata. In other words, it is a general-purpose graph database, and it is no coincidence that it is the leading product in this space.

The Bottom Line

Whenever we talk to a vendor in the graph database space it is Neo4j they compare themselves to. Even if they do something different and address a different market, Neo4j is the benchmark – the company claims more than 400 enterprise customers globally. In pretty much every instance Neo4j should be on your shortlist.