Archived Sansa Query
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Sansa Stack | 139 | 5 months ago | 36 | apache-2.0 | Scala | |||||
| Big Data RDF Processing and Analytics Stack built on Apache Spark and Apache Jena http://sansa-stack.github.io/SANSA-Stack/ | ||||||||||
| Rdf2x | 35 | 4 years ago | 4 | apache-2.0 | Java | |||||
| RDF2X converts big RDF datasets to the relational database model, CSV, JSON and ElasticSearch. | ||||||||||
| Archived Sansa Query | 31 | 4 years ago | apache-2.0 | Scala | ||||||
| SANSA Query Layer | ||||||||||
| Geotriples | 31 | 3 years ago | 14 | apache-2.0 | Java | |||||
| Publishing Big Geospatial data as Linked Open Geospatial Data | ||||||||||
| Sparqlgx | 28 | 3 years ago | 1 | other | OCaml | |||||
| Efficient Distributed Evaluation of SPARQL with Apache Spark | ||||||||||
| Sansa Notebooks | 25 | 4 years ago | 1 | apache-2.0 | Makefile | |||||
| Interactive Spark Notebooks for running SANSA examples. | ||||||||||
| Sparksqlrdfbenchmarking | 10 | 2 years ago | 1 | cc0-1.0 | Scala | |||||
| A systematic Benchmarking on the performance of Spark-SQL for processing Vast RDF datasets | ||||||||||
| S2rdf | 8 | 6 years ago | 2 | apache-2.0 | Java | |||||
| S2RDF (SPARQL on Spark for RDF) is a SPARQL query processor for Hadoop based on Spark SQL. It uses the relational interface of Spark for query execution and comes with a novel partitioning schema for RDF called ExtVP (Extended Vertical Partitioning) that is an extension of the Vertical Partitioning (VP) schema introduced by Abadi et al. ExtVP enables to exclude unnecessary data from query processing by taking into account the possible relations between tables in VP. | ||||||||||
| Spark Rdf Statistics | 6 | 5 years ago | apache-2.0 | Scala | ||||||
| Distributed RDF Statistics | ||||||||||
| Prost | 5 | 4 years ago | 3 | mit | Java | |||||
| RDF storage and SPARQL processing on top of Apache Spark. | ||||||||||
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