RDFox Reviews & Product Details - Page 2

RDFox is a "lean and mean" semantic graph database, Oxford Semantic Technologies clearly understands what the key priorities are for anyone who wants to deploy a database in production: it has to be fast, reliable and predictable. Many of their competitors focus on adding more and more (often proprietary) features forgetting (a bit) about these three key priorities.

RDFox has a radically different design than other semantic graph databases in the sense that it is an "in-memory" database (with full ACID transaction support) which means that it is screaming fast (many LUBM queries are more than a 1000 times faster than the nearest competitor) but it also means that it really needs a lot of memory for large datasets.

Fortunately, if you'd be building an Enterprise Knowledge Graph (EKG) according to the 10 principles of the EKGF (see https://ekgf.org/principles) you would not need to have all your datasets in just one database instance and could freely scale horizontally. RDFox would allow you to support real-time use cases like pre-trade risk calculation or other advanced use cases using many complex datasets. Review collected by and hosted on G2.com.

No support for clustering yet. I believe that feature is coming soon though. Review collected by and hosted on G2.com.

I like the following features of RDFox:

1. server- datastore archtiecutre

2. multi-threading and sophisticated indexing

3. flexible rule language with negation and aggregation

4. fast incremental updates

5. explanation of inferences

6. monitoring rule evalaution process Review collected by and hosted on G2.com.

Some further improvements:

1. rule mangement: rule editor, dependency graph,

2. rule2sparql translation (at least for basic structure), which will help to debug the rules using SPARQL queries.

3. datastore priority configation

4. SPARQL console can return the total number of rows. Supporting the shortcut key (crl+/) for commenting on the SPARQL queries. Review collected by and hosted on G2.com.

I love the incremental reasoning engine. Aside from this - I like that I can create a start script to automate initialisation, and the visualisation studio. I have loaded some fairly large datasets and RDFox remains very fast. Review collected by and hosted on G2.com.

The documentation has been unclear at times. However, my questions have always been answered quickly (and the documentation updated after that). Review collected by and hosted on G2.com.

High-performance SPARQL querying and Datalog reasoning even with large datasets. In-store SHACL engine that is easy to use. We integrate our software platform and develop real-time recommender use cases, which are made possible because of the fast incremental reasoning. Review collected by and hosted on G2.com.

I would apprechiate SPARQL update for the Web UI. Review collected by and hosted on G2.com.