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Comparing Grakn to Semantic Web Technologies — Part 2/3

This is part two of Comparing Semantic Web Technologies to Grakn. In the first part, we looked at how RDF compares to Grakn. In this part, we look specifically at SPARQL and RDFS.

SPARQL

What Is SPARQL?

SPARQL is a W3C-standardised language to query for information from databases that can be mapped to RDF. Similar to SQL, SPARQL allows to insert and query for data. Unlike SQL, queries aren’t constrained to just one database and can be federated across multiple HTTP endpoints.

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Comparing Grakn to Semantic Web Technologies — Part 1/3

This article explores how Grakn compares to Semantic Web Standards, focusing specifically on RDF, XML, RDFS, OWL, SPARQL and SHACL. There are some key similarities between these two sets of technologies - primarily as they are both rooted in the field of symbolic AI, knowledge representation and automated reasoning. These similarities include:

  1. Both allow developers to represent and query complex and heterogeneous data sets

  3. Both give the ability to add semantics to complex sets of data
  4. Both enable the user to perform automated deductive reasoning over large bodies of data

However, there are core differences between these technologies, as they were designed for different types of applications. Specifically, the Semantic Web is built for the Web, with incomplete data coming from many sources, where anyone can contribute to the definition and mapping between information sources. Grakn, in contrast, wasn't built to share data over the web, but instead to work as a transactional database for closed world organizations. Because of this, comparing the two technologies sometimes feels like comparing apples to oranges.

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Graph Explosion and Consolidation. The Year of the Graph Newsletter: June 2019

With the knowledge graph space exploding on all accounts (interest, use cases, funding), centrifugal and centripetal forces are simultaneously at play. While the "wild, early days" of knowledge graph technology are gone, the 20 year anniversary of the Semantic Web is a good opportunity to reflect on what worked and what didn't and to move forward in a pragmatic way.

A testament to the fact that this space is booming: more offerings are available every day, the quality and quantity of knowledge sharing is rising to meet the demand, and at the same time we are starting to see consolidation — in vendors, models, and standards.