Semagrow is a Query Federation engine that is both algorithmically sophisticated and well-engineered and has been shown to outperform all other federated querying engines on both standard benchmarks and our own use cases.

Semagrow allows combining, cross-indexing and, in general, making the best out of all public data, regardless of their size, update rate, and schema: Semagrow offers a single SPARQL endpoint that serves data from remote data sources and that hides from client applications heterogeneity in both form (federating non-SPARQL endpoints) and meaning (transparently mapping queries and query results between vocabularies).

The Semagrow query planner exploits metadata about the nodes of the federation to optimize query execution. Semagrow allows full flexibility on the level of detail of this metadata, and exhibits pay-as-you-go behaviour where robustness to lack of detail and accuracy of the metadata is matched with the quality of the optimization in the presence of detailed and accurate metadata.

To run Semagrow issue

docker run -p <host_port>:8080 semagrow/semagrow

Then you can access it from

http://localhost:<host_port>/SemaGrow/

Semagrow configuration files are located at

/etc/default/semagrow

to add external configuration files run Semagrow as

docker run -p <host_port>:8080 -v <local_dir>:/etc/default/semagrow semagrow/semagrow

To add a new node to the Semagrow federation follow the instructions at http://semagrow.github.io/configuration/