'What is is the simplest way to setup a local rdf triple store with SPARQL endpoint?
For learning SPARQL it might be useful to have full control both over the query text and the data (RDF triples). While there are many public SPARQL endpoints available their data is typically read-only for obvious reasons. To actively apply SPARQL-queries to ones own data, a local triple store might be useful, e.g. for reproducing the examples from https://www.w3.org/TR/rdf-sparql-query/.
However, setting up such an infrastructure with all its dependencies might be complicated.
→ What is the simplest¹ way to setup a local triple store with SPARQL endpoint on a usual PC?
(¹: The meaning of "simplest" depends on ones system configuration and prior knowledge, which can be reflected by different answers.)
Solution 1:[1]
A java based solution is:
https://jena.apache.org/download/index.cgi
Down the Apache Jena Fuseki zip.
Unpack the zip, run fuseki-server.
Goto http://localhost:3030/
Solution 2:[2]
If one has already a Python environment then rdflib-endpoint provides a simple solution with only two commands
pip install rdflib-endpoint(run once)rdflib-endpoint serve <path_to_your_triple-file(s)>- Access the YASGUI SPARQL editor on http://localhost:8000
Solution 3:[3]
Maybe https://triplydb.com is interesting for you. You can create datasets like this. https://triplydb.com/Triply/linkedmdb/sparql/linkedmdb
Solution 4:[4]
Using Eclipse RDF4J via docker:
docker pull eclipse/rdf4j-workbench:latest
docker run -p 8080:8080 eclipse/rdf4j-workbench:latest
and then access at http://localhost:8080/rdf4j-workbench
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | AndyS |
| Solution 2 | cknoll |
| Solution 3 | Benjamin Hofstetter |
| Solution 4 | Jeen Broekstra |