Ontotext, the Bulgarian software developer focused on organisational semantic knowledge, has rolled out an update to its graph database, GraphDB 9.1.
First among additional features is support for Shapes Constraint Language (SHACL), a World Wide Web Consortium specification for validating graph-based data against a set of conditions.
Ontotext's GraphDB is a resource description framework (RDF) database, making it well adapted to semantic applications. Alternatives include labelled property graph databases, such as the most popular graph database (ahem, graph company), Neo4j.
Vassil Momtchev, Ontotext CTO and GraphDB product manager, told The Register: "Property graph databases are easy to start with, but they work on notions about schemas. These notions might work in some situations, but not all. These are the schema-level constraints of this approach."
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He said the support for SHACL allows GraphDB 9.1 to validate the data against the schema each time new data is loaded to the database.
"Data quality is obviously important. You can enforce the quality of the data only if you have a schema of the information. SHACL validation allows you to define rules for the validity of the data around the schema. Otherwise, you need to run some queries every time you load data to check if the data is still good for the database."
The upshot is delivery of applications on the GraphDB 9.1 will be cheaper and faster than on databases without SHACL support, he claimed.
The second improvement to the flagship product helps users tracking changes in the current or past database transactions. This way, GraphDB will maintain a configurable provenance of all knowledge graph updates.
"This is the provenance of knowing when information becomes available, and when it was needed and also when it was deleted," Momtchev said.
Lastly, GraphDB supports Kerberos, a network authentication protocol, for the first time in its 9.1 iteration, avoiding the need to store passwords on client computers.
The aim of applying graph database technology to enterprise data is to try to overcome the age-old problem of accessing latent organisational knowledge; something knowledge management software once tried to address. It's also a growing thing: Industry analyst Gartner said in November the application of graph databases will "grow at 100 per cent annually over the next few years".
GraphDB is ranked at eighth position on DB-Engines' list of most popular graph DBMS, where it rubs shoulders with the likes of tech giants such as Microsoft, with its Azure Cosmos DB, and Amazon's Neptune.
"GraphDB is very good at text analytics because any natural language is very ambiguous: a project name could be a common English word, for example. But when you understand the context and how entities are connected, you can use these graph models to disambiguate the meaning," Momtchev said.
Tom Zeppenfeldt, founder of graph database application developer Graphileon, welcomed the new features in GraphDB 9.1: "With more complex graphs, data integrity is key. So, support for SHACL is really something very useful. Since you have more and more use of graph in AI, where you want to explain what is in the black box, data integrity and quality are crucial," he said. ®