Halyard
Halyard is a free, open-source RDF store for large semantic data models, with named graph support and SPARQL 1.1 querying of Linked Data snapshots.
What Halyard is
Halyard is a free, open-source RDF store for large semantic data models, with named graph support and SPARQL 1.1 querying of Linked Data snapshots. Written in Java, it is built on Eclipse RDF4J and Apache HBase, and stores datasets as HBase tables; multiple repositories can point to one shared dataset. Deployment is documented for Amazon Elastic MapReduce or an Apache Hadoop cluster node configured with an HBase client. Bulk Load uses MapReduce to bring RDF from HDFS into HBase, accepting formats including Turtle, RDF/XML, N-Triples, TriG, N-Quads, and JSON-LD. Command-line tools support SPARQL updates, exports, parallel bulk updates, and deletion of triples or named graphs. Queries can use RDF4J Console, RDF4J Workbench, or RDF4J Server endpoint REST APIs. Halyard Stats calculates dataset statistics, and an optional Elasticsearch index can support text searches across dataset literals. Halyard Endpoint launches a SPARQL endpoint; Halyard Summary is an experimental MapReduce tool for producing approximate dataset summaries. Hadoop and HBase are runtime requirements and are not bundled. On secured clusters, Console use requires kinit authentication.
Good
- Free and open source.
- Supports SPARQL 1.1 and named graphs.
- Bulk loading accepts several RDF formats.
- Provides tools for updates, exports, and deletion.
- Multiple repositories can use a shared dataset.
Watch out
- Hadoop and HBase are not bundled.
- Requires Hadoop 2.5.1 or later, HBase 1.1.2 or later, and Java 8.
- Federation does not recognize external SPARQL endpoint service types.
- Halyard Summary is experimental.
Who it suits
Halyard suits teams managing large RDF datasets who can provide Hadoop and HBase and need named graphs, bulk data tools, and SPARQL 1.1 access. Its deployment documentation focuses on Amazon EMR or Hadoop cluster environments.
Verdict
Halyard offers a set of RDF storage, bulk data, and SPARQL query tools for Hadoop and HBase environments. Check the runtime requirements and shared-dataset deletion behavior before deployment.
The facts
Each one read from Halyard's own pages, with the date it was checked.
What it does
- Bulk data tools
- Its command-line and MapReduce tools support bulk loading and exporting RDF data, dataset statistics, SPARQL updates, and deletion of large sets of triples or named graphs.checked 8 Oct 2026
- Bulk loading
- Halyard Bulk Load uses MapReduce to load RDF data from HDFS into HBase, and the documented input formats include Turtle, RDF/XML, N-Triples, TriG, N-Quads, and JSON-LD.checked 8 Oct 2026
- Data deletion behavior
- Deleting a repository configuration does not delete its Halyard dataset, while clearing the repository or deleting statements affects the shared data for all users.checked 8 Oct 2026
- Data management
- Command-line tools support SPARQL Update, parallel bulk updates, export, and bulk deletion of triples or named graphs.checked 8 Oct 2026
- Data storage
- Halyard datasets are stored as HBase tables, and multiple repositories can point to one shared dataset.checked 8 Oct 2026
- Deployment
- The maker documents deployment on Amazon Elastic MapReduce or on an Apache Hadoop cluster node configured with an Apache HBase client.checked 8 Oct 2026
- Endpoint
- Halyard Endpoint is a command-line application for launching a SPARQL endpoint to serve queries.checked 8 Oct 2026
- Experimental feature
- Halyard Summary is described as an experimental MapReduce application that calculates an approximate dataset summary and exports it to a file.checked 8 Oct 2026
- Federation limit
- Federated queries can span Halyard datasets using SPARQL SERVICE, but external SPARQL endpoint service types are not recognized.checked 8 Oct 2026
- Implementation
- Halyard is written in Java and is based on Eclipse RDF4J and Apache HBase.checked 8 Oct 2026
- Not bundled
- Apache Hadoop and Apache HBase components are not bundled with Halyard and must be available in the runtime environment.checked 8 Oct 2026
- Product
- Halyard is a horizontally scalable RDF store with named graph support, designed for very large semantic data models and SPARQL 1.1 queries over Linked Data snapshots.checked 8 Oct 2026
- Purpose
- Halyard is a horizontally scalable RDF store with named graph support for storing and integrating large semantic data models and querying linked data snapshots with SPARQL 1.1.checked 8 Oct 2026
- Querying
- The included RDF4J Console can evaluate SPARQL queries and connect to local or remote repository endpoints.checked 8 Oct 2026
- Query interface
- Halyard supports SPARQL access through RDF4J Console, RDF4J Workbench, and RDF4J Server SPARQL endpoint REST APIs.checked 8 Oct 2026
- RDF formats
- Bulk Load accepts RDF4J RIO-supported formats including N-Triples, RDF/XML, Turtle, TriG, N-Quads, and JSON-LD, with Hadoop-supported compression codecs.checked 8 Oct 2026
- Runtime requirements
- The getting-started page lists Apache Hadoop 2.5.1 or later, Apache HBase 1.1.2 or later, and Java 8 Runtime as requirements.checked 8 Oct 2026
- Search integration
- An optional supplementary Elasticsearch index can index dataset literals to provide more advanced text search features.checked 8 Oct 2026
- Security behavior
- On a secured cluster, the RDF4J Console instructions say to authenticate with kinit credentials before use.checked 8 Oct 2026
- Statistics
- Halyard Stats calculates dataset statistics and stores them in a named graph or exports them to a file.checked 8 Oct 2026
- Storage modes
- For Amazon EMR deployments, HBase can use HDFS or S3 storage.checked 8 Oct 2026
- Support
- The home page links to documentation, open GitHub issues, a discussion group, and lists Adam Sotona as the author contact.checked 8 Oct 2026
- Technology
- Halyard is written in Java and built on Eclipse RDF4J and Apache HBase.checked 8 Oct 2026
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