GraphDB

GraphDB is a semantic graph database for organizations that need RDF-based relationships, SPARQL querying, and inferred meaning across fragmented data. It suits knowledge-graph teams, data architects, and AI projects that can work within a single core at no cost, while larger production deployments need Enterprise. The main trade-off is clear: the free edition preserves standards support but not the processing and availability features intended for scaled operations.

Overview

GraphDB links business data as an RDF graph and uses semantic search and real-time inferencing to derive connections that are not explicitly stored. Ontology modeling, semantic reasoning, graph visualization, and SPARQL querying make it a serious fit for standards-led knowledge-graph work rather than a generic document database.

Graphwise was formed in 2024 through the combination of Semantic Web Company and Ontotext. Its offices include Vienna, Sofia, London, New York, and Basel, with main offices described in Sofia, Vienna, and New York City.

Key features

Free and Enterprise both support RDF 1.1, SPARQL 1.1, RDF-Star, and SPARQL-Star, plus reasoning for RDFS, OWL 2 RL, and OWL 2 QL. That standards coverage helps teams preserve interoperable semantic models and use inference to expose related facts. SPARQL is the query language, so projects built around other graph-query paradigms will need to adapt.

Import support spans Turtle, Turtle-star, N-Triples, N-Quads, JSON-LD, NDJSON-LD, RDF/JSON, RDF/XML, TriX, TriG-star, and BinaryRDF. The range is useful when consolidating heterogeneous RDF sources, while ontology modeling and visualization support the work of designing and explaining a graph.

GraphRAG, MCP support, no-code RAG chat in Workbench, precision entity linking, and natural-language graph queries from LangChain target AI-assisted discovery over connected data. They are most relevant when a team already has a semantic graph and wants language-model access to it, not when the requirement is simply transactional storage.

Integrations include MongoDB, Kafka, JDBC, GraphQL, SQL-accessible data virtualization, and connectors for Lucene, Elasticsearch, and Solr. These options make GraphDB easier to place in an existing data estate, especially for streaming, search, and relational access.

Pricing

GraphDB Free

free for a single-core license. It is the sensible entry point for individual developers, prototypes, education, and modest workloads that can accept one core. Starting with GraphDB 11.0.0, even this edition requires a valid license, although the license can be requested for free.

GraphDB Enterprise

Enterprise uses custom pricing and is licensed for 12 or more cores. It adds concurrent loading, querying, and inference; parallel query processing; cluster failover, synchronization, and load balancing. Those capabilities matter for busy shared services and resilient production clusters, but buyers must obtain a quote before comparing total cost.

Enterprise is available on-premise from Graphwise and its partners. A 12-core cluster edition is also offered as SaaS through AWS Marketplace and Microsoft Azure Marketplace. Community support applies to both editions, with an optional commercial SLA for Enterprise.

Platforms

GraphDB supports API, Linux, macOS, self-hosted deployment, web access, and Windows. Downloads include Windows MSI, macOS Apple Silicon and Intel DMG packages, Linux RPM and DEB packages, and a platform-independent server distribution. This combination suits teams that want local development alongside self-managed servers, while the marketplace cluster option provides a managed Enterprise route.

Who it's for

Choose GraphDB Free for standards-based knowledge graphs, semantic search, ontology work, and AI experiments that fit a single core. It is particularly suitable for teams importing varied RDF formats and connecting existing databases, streams, and search systems.

Choose Enterprise when concurrent processing, high-core licensing, failover, synchronization, load balancing, or a commercial SLA is essential. It is less suitable when you need unrestricted free-edition scaling or a published Enterprise price for straightforward budgeting.

Pros and cons

• Pro: Broad RDF, SPARQL, RDF-Star, and OWL reasoning support serves interoperable semantic projects.
• Pro: Numerous import formats and connectors reduce friction when assembling data from databases, streams, APIs, and search indexes.
• Pro: GraphRAG, MCP, Workbench RAG chat, entity linking, and LangChain queries address modern AI access patterns.
• Con: Free is restricted to a single core, limiting its appeal for sustained parallel workloads.
• Con: Enterprise pricing is custom, so purchase planning requires a direct quote.
• Con: A valid license is required for every edition from version 11.0.0, including Free.

Alternatives

For a broader application-development platform with Android and iOS support, consider Mendix; its Free plan allows one deployment environment per application.

RDFox is worth choosing when a 30-day, non-commercial evaluation license is the priority.

Choose AllegroGraph if a free tier capped at five million triples better matches the project.

Protégé is the straightforward free, open-source option for OWL 2 ontology work.

RDF Studio offers a free semantic data workspace without stated price or usage limits.

Choose Stardog when a renewable one-year free license with up to one million stored edges and three databases fits.

TypeDB is an alternative for a fully managed dedicated server with a 10 GB, 8 GB RAM, and 2 vCPU free allowance.

Eclipse RDF4J suits developers seeking a free, open-source Java framework for RDF applications.

See the Knowledge Graph Software category for more options.

Verdict

GraphDB is a strong choice for teams that need standards-compliant RDF and SPARQL, semantic inference, and an unusually broad set of data and AI integrations. Start with Free for single-core development and smaller graphs; move to Enterprise when concurrency and cluster resilience justify a quote. Look elsewhere if a free edition must scale beyond one core or if predictable, published Enterprise pricing is essential.