SPARQL 1.1 Now Supported
September 7th 2011 by
The top feature request we’ve heard from our users and customers lately has been support for SPARQL 1.1. We’ve listened, and are pleased to announce that Dydra now implements SPARQL 1.1 Query and Update in full.
SPARQL 1.1 Query
We now fully support SPARQL 1.1 Query, including aggregates, subqueries, negation and filtering, SELECT expressions, property paths, assignments and bindings, syntactic sugar for CONSTRUCT, and many additional operators and functions.
Signing up for a Dydra account is the very easiest way to get to grips with the new features in SPARQL 1.1. Our easy-to-use browser-based query editor lets you interactively write and test queries on your dataset without any hoops to jump through to install complex software or to configure and serve a SPARQL endpoint yourself.
SPARQL 1.1 Update
We also now fully support SPARQL 1.1 Update. Starting today, you can use all of the update operators on your repository data: INSERT/DELETE, INSERT DATA, DELETE DATA, LOAD, CLEAR, CREATE, DROP, COPY, MOVE, and ADD.
We will in the near future be updating our documentation with further details regarding the transactional semantics of Dydra, since the official SPARQL 1.1 Update specification leaves them up to each implementation.
We’ve improved our query engine’s performance quite a bit. It was already pretty fast before, and it’s yet faster now. In particular, we’ve improved the throughput for “worst-case” queries that perform a lot of full edge scans of large repositories. These kinds of queries can now run even up to a hundred times faster.
This is, indeed, one of the benefits of hosting your SPARQL endpoint with Dydra: as we simultaneously both roll out ever more hardware capacity and work to further improve our query engine, you reap the benefits without having to lift a finger.
Last but not least, we’ve overhauled how we do data imports. We now make use of the very latest release of the Raptor RDF Syntax Library, the high-performance, open-source library for parsing and serializing most RDF serialization formats as well as RSS/Atom feeds and various microformats.
Anything that Raptor can parse, Dydra can now import into your repository. The new import functionality is also considerably faster than what we offered before.
We intend to keep our internal Raptor build closely in sync with the upstream open-source release, which means that the best way to ensure Dydra can import some new format or another is to contribute to the Raptor project on GitHub.blog comments powered by Disqus