The Stardog Blog
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Stardog makes the Enterprise Knowledge Graph fast and easy. We’re going to build a Java app that talks to Stardog’s RDF graph database in 5 easy steps.
Stardog’s web team has been experimenting with the Serverless Framework to prototype a web app with a pure AWS infrastructure. Serverless is to apps what baskets are to eggs, basically.
Stardog is part of NASA’s mission to Mars and we couldn’t be prouder of that. In this post I’ll explain some of the how and the why.
Working with Stardog should be easy and fun, no matter what your tool chain looks like. So I’m building extensions in Visual Studio Code for Stardog, and I’m kinda lovin’ it.
We’re adding graph traversal to Stardog to support a broader range of graph queries and analysis. Now that we’ve figured out how to extend SPARQL solutions, we can more easily make Stardog traverse graphs to find paths and other relationships.
Stardog Cluster provides a highly-available platform that can be distributed across multiple servers in your infrastructure. We’ve implemented a kind of controlled chaos testing to get there.
We’re extending Stardog’s knowledge graph capabilities to include arbitrary graph algorithms that aren’t easily expressed in SPARQL. But first we have to fix SPARQL solutions.
We’re moving the Stardog community support forum from Google to Discourse, and we’re adding comments to this blog.
The main problem of all heavily-loaded Java applications which operate on a huge amount of data is memory management. We solve this problem with a new, byte-based memory management scheme that will debut in the upcoming Stardog 5 release.
We think the user experience is crucial, even when dealing with something as complex as a highly available cluster system. So we made Stardog Graviton.
In Reactive, Streaming Stardog Kernel, we looked at the design of and motivations for upcoming changes to the SNARL API. In this post we look at the new API in detail.