But what about performance, and ease of use? A 3rd party evaluation shows Gremlin to be comparable e.g. Gremlin offers portability across the spectrum, including SQL. It has however formed the basis for an alternative approach to querying RDF graphs, called HyperGraphQL. GraphQL mostly resembles a different approach to REST APIs, and is limited in what it can express in terms of graph constructs, as it only supports trees. But it can be argued that GraphQL is not exactly a graph query language. GraphQL has a few things going for it: it has been created and supported by Facebook, and it has an open specification and an intuitive syntax. Then there are a number of vendor-specific query languages, and GraphQL. Cypher started out as Neo4j's query language and spawned the openCypher project, with support from SAP Hana Graph and Redis Graph among others. SPARQL is a W3C standard that works with RDF native graphs as well as other sources including relational databases using a mapping bridge. There is a number of graph query languages out there at the moment besides Gremlin, with SPARQL and Cypher being the two most prominent ones. In a nascent market such as graph databases, with over 30 different options and without the equivalent of SQL - a standard, universally accepted query language in the relational database world, this is an important point. This means that TinkerPop can act as a layer that bridges different graph systems, with queries written in Gremlin reusable across implementations. Furthermore, all TinkerPop-enabled systems integrate with one another allowing them to easily expand their offerings as well as allowing users to choose the appropriate graph technology for their application". "When a data system is TinkerPop-enabled, its users are able to model their domain as a graph and analyze that graph using the Gremlin graph traversal language. TinkerPop is an open source, vendor-agnostic, graph computing framework, that comes with its own graph querying language, Gremlin. Rodriguez describes it as a match made in heaven, and Titan as having proved to be very successful not only for their clients, but also for the general public which were in need of such technology.įor the last 3 years, while with DataStax, Rodriguez has been developing Apache TinkerPop3, along with colleagues Stephen Mallette and Daniel Kuppitz. The team pushed heavy to create and promote Titan which was a mix of the ideas of Bröcheler / LaRocque (graph structure) and Mallette / Rodriguez (graph process). Bröcheler and LaRocque were interested in developing a commercial version a distributed graph database based on big table technologies such as Cassandra and HBase, and Rodriguez says the timing could not have been better. Rodriguez and Mallette met Matthias Bröcheler and Dan LaRocque, and thus Titan was born. The company grew fast and they were noticing a trend - the contracts they were getting were requiring scalable graph technologies and at the time, according to Rodriguez, nothing of the sort existed in the market. Thus, Aurelius was founded in order to handle the growing need for graph expertise in industry, by Rodriguez and Stephen Mallette.
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