Claiming that RDF triplestores are typically used for offline analytics suggest unfamiliarity with their most popular use cases. Triplestores are often used in very dynamic operational database setups such as metadata-based content management at world’s largest media and publishers like BBC, FT, Wiley, Elsevier, Oxford University Press and DK.
As new approaches to data management are gaining popularity, we start seeing more texts that compare the different NoSQL and particularly graph database engines. A recent example is “Graph Databases for Beginners: Other Graph Data Technologies”.
While such comparisons do a great job helping developers understand “how stuff works” sometimes they tend to be imprecise when authors comment engines beyond their core area of expertise. The post referred above makes statements about triple stores, also called semantic graph databases, like these:
“However, triple stores are not “native” graph databases because they don’t support index-free adjacency, nor are their storage engines optimized for storing property graphs.”
“… the most common use case for triple stores is offline analytics rather than for online transactions”.
And my 20+ years of piled up expertise urges me to comment.
To provide a bit of background, let’s start with:
- Triplestores are graph database engines that, unlike engines based on Property Graphs, implement a set of comprehensive, vendor-independent standards: RDF (the data model), RDFS and OWL (schema languages) and SPARQL (query language).
- Triplestores work with globally unique identifiers – together with few other features, this makes them very suitable for integration of data – be it the thousands Linked Open Data datasets or proprietary data.