Halyard
Halyard: A Hadoop- and HBase-oriented RDF store for distributed semantic data workloads. Ranked #15 of 26 in RDF Databases by our editors (7.7/10); pricing: Open source; best for horizontally scalable RDF on Hadoop or HBase.
At a glance
- Editor score7.7 / 10
- PricingOpen source
- Best forHorizontally scalable RDF on Hadoop or HBase
- Paid fromFree
- Deployment optionsHybrid
- Facts checked21 Sep 2026

Where it wins
- Apache HBase-backed storage supports horizontal RDF scaling
- SPARQL 1.1, named graphs, federation, and REST APIs
- Bulk loading and parallel export use Hadoop MapReduce tools
Where it doesn't
- Requires teams comfortable operating Hadoop and HBase infrastructure
- Documentation appears substantially dated
- Elasticsearch indexing and search are optional rather than core
Our verdict on Halyard
Halyard is an open-source RDF triplestore built for very large semantic data models and Linked Data snapshots. It stores RDF datasets in Apache HBase and is aimed at teams already operating Hadoop or HBase infrastructure, including deployments on Amazon EMR. Its web, Linux, macOS, API, and self-hosted access options support both service-based and command-line workflows.
Its ecosystem fit is a central strength. Halyard connects Apache HBase storage with Apache Hadoop processing, Eclipse RDF4J services, Amazon EMR deployments, and optional Elasticsearch literal indexing and search. RDF4J Server provides a SPARQL endpoint and REST APIs, while RDF4J Workbench supplies a web interface. The platform supports SPARQL 1.1 querying and updates, named graphs, federated queries across Halyard datasets through SPARQL SERVICE, and a broad set of RDF formats including Turtle, RDF/XML, N-Triples, TriG, N-Quads, JSON-LD, and others.
Halyard is more focused than a general-purpose RDF database: its architecture and operational model center on distributed Hadoop and HBase environments. Bulk loading and parallel export through Hadoop MapReduce tools make it suitable for large ingestion and movement workflows, while optional Elasticsearch support adds a separate path for literal search. Teams seeking a tightly integrated Hadoop/HBase RDF stack should consider Halyard; teams wanting a simpler deployment model or a narrower standalone triplestore are likely to prefer an alternative. The substantially dated documentation also makes current implementation planning an important consideration.
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Halyard pricing
Halyard fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Free |
| Deployment options | Hybrid |
| SPARQL support | Sparql 1.1 |
| Reasoning support | Not verified |
| RDF-star support | Not verified |
| Federated queries | Yes |
| Supported RDF formats | N-Triples, RDF/XML, Turtle, N3, RDF/JSON, TriG, N-Quads, BinaryRDF, TriX, JSON-LD |
| Deployment | Cloud, Self-hosted |
| Platforms | Web, Linux, macOS |
| Support | Community, Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 5 integrations: Apache HBase, Apache Hadoop, Eclipse RDF4J, Amazon EMR, Elasticsearch |
| Pricing | Open source |
| Website | merck.github.io |
| Facts checked | 21 Sep 2026 |
Halyard integrations
Halyard lists 5 integrations on its own site.
- Apache HBase
- Apache Hadoop
- Eclipse RDF4J
- Amazon EMR
- Elasticsearch
Alternatives to Halyard
- GraphDBA broad RDF platform with a free edition and enterprise-grade deployment options.9.3
- AllegroGraphA broad RDF platform for reasoning, federation, analytics, and vector-enabled knowledge graphs.9.1
- StardogA broad enterprise platform for federated queries, virtual graphs, and semantic reasoning.9.0
See all Halyard alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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