RDF Graph Database-as-a-Service with S4

A few weeks ago we opened to developers a beta version of the RDF Database-as-a-Service (DBaaS) on the Self-Service Semantic Suite (S4) platform. The DBaaS is based on GraphDB – our enterprise grade RDF graph database providing high-performance querying over large volumes of RDF data. The DBaaS version of GraphDB running on the S4 platform is the perfect solution for scenarios with small or medium database size and query load, where investing in software licenses and provisioning and maintaining an on-premise 24/7 server is not cost optimal.

With our RDF DBaaS, developers can have their private database instance up and running within seconds and they will no longer need to deal with DBA specific tasks such as installation and upgrades, provisioning and deployment, backups and restores, as well as ensuring the database availability. Just like the other key components of the S4 platform – the text analytics & knowledge graphs available as-a-service – the RDF database-as-a-service is instantly available and easily accessible, so that developers can build smart data prototypes faster and at a lower cost, without spending valuable time on installing, configuring, or even developing their own infrastructure components.

The RDF DBaaS on S4 will be available in various configurations (currently only the Micro instances are open to developers):

  • Micro, of up to 1 million triples (available for free)
  • XS, of up to 10 million triples
  • S, of up to 50 million triples
  • M, of up to 250 million triples
  • and L, of up to 1 billion triples

Of course we provide options for managing even larger volumes of RDF data via the self-managed RDF database in the Cloud, available on the AWS Marketplace.

Database instances can be created and deployed within seconds from the simple web interface on the S4 website:


After a database is created and deployed, it is available to developers and applications via a standard OpenRDF REST API and a standard SPARQL query endpoint. Various tools which provide RDF database management via the OpenRDF API, such as the OpenRDF Workbench or the GraphDB Workbench, can be used to import data into the DBaaS or to perform simple data exploration and querying. Tools which provide RDF exploration & visualisation, such as Graph Rover or Information Workbench, will also seamlessly work with the SPARQL endpoint exposed by the DBaaS.

On Jun 11th we held a webinar “On-demand RDF Databases in the Cloud” where we demonstrated how to instantly create and deploy a fully managed DBaaS running on S4, then import & query data with the OpenRDF Workbench, and finally explore & visualise data with the Metreeca Graph Rover. The webinar recording is available here.

If you haven’t already done so, register for a free developer account for the Self-Service Semantic Suite, take a look at the developer’s documentation, create and configure your own RDF graph database in the Cloud and start building smart data prototypes!

Marin Dimitrov

Marin Dimitrov

CTO at Ontotext
As the technological captain of Ontotext, he is leading the company on the right tech route and reserving our spot on the map of the world. His sharp mind can explain complex things in a simple way, making him an invaluable resource in semantics. Marin is a frequent speaker on semantic conferences and open data meetups at various technology related events.
Marin Dimitrov

Related Posts

  • Featured Image

    The New Cache on the Block: A Caching strategy in GraphDB To Better Utilize Memory

    The ability to seamlessly integrate datasets and the speed at which this can be done are mission critical when it comes to working with big data. The new caching system of GraphDB is better, faster and smarter and solves the issues of the old caching strategy in GraphDB.

  • Datathon Case Overview: Revealing Hidden Links Through Open Data

    For the first Datathon in Central and Eastern Europe, the Data Science Society team and the partner companies provided various business cases in the field of data science, offering challenges to the participants who set out to solve them in less than 48 hours. At the end of the event, there were 16 teams presenting their results after a weekend of work.

  • Featured Image

    What is GraphDB and how can it help you run a smart data-driven business?

    Learn about GraphDB through the solutions it offers in a simple and easy to understand way. In this presentation we have unpacked GraphDB for you, using as little tech talk as possible. Read on and see what Ontotext’s semantic graph database has to do with pasta making.

Back to top