Create a flexible semantic layer that connects enterprise data, enriches it with business meaning, and makes it reusable across AI, analytics, search, and applications.
Knowledge Graphs are built to represent real-world entities and their complex relationships to one another. Compared to the rigidity of a relational database structure, a Knowledge Graph can maintain multiple points of view simultaneously.
There’s always more data — new external data streams, new data sources needed for the next release, new acquisitions with their own messes of data. Stardog’s extensible data model easily incorporates new sources while maintaining original schemas and metadata.
Encode hierarchical relationships, properties, and metadata into your Knowledge Graph. Query your unified data to discover deep connections, uncover patterns within the data, and get definitive, explainable results.
Virtualization offers low-impact access to your disparate data, whether it’s on-prem or in the cloud. Access your data without moving or copying it, avoiding data proliferation while protecting original ownership and governance.
Connect and query data of any structure
Connect and query data of any structure
Virtualize or materialize
Inference Engine for explainable AI
Built-in AI and ML
Navigate your data with Explorer
Data quality management
Based on open standards
High-performance graph database
Connect and query data of any structure
A knowledge graph is only as powerful as the data it can access, so we’ve built database connectors to make it easier to unify your data. Stardog has connectors for all major SQL systems and the most popular NoSQL databases. In addition, we built the BITES pipeline to process your unstructured data like research papers, resumes, and press releases. BITES uses NLP entity recognition to identify and extract concepts, adding those data relationships into the knowledge graph. Once your data is unified in Stardog, you can see a 360-degree view on each data point.
Virtualize or materialize
Stardog supports completely seamless virtualization and materialization so you can access any data, whether it’s on-prem or in the cloud. Where other data management tools force you into rigid access patterns, Stardog lets you choose to materialize or virtualize based on what’s best for your data and to optimize for performance or cost requirements. No other platform combines Knowledge Graphs with virtualization; the resulting Virtual Graphs offer unprecedented power and flexibility to investigate deep connections across data sources.
Inference Engine for explainable AI
Stardog’s Inference Engine allows you to harmonize conflicting data definitions without changing or copying the underlying data. Capture your business and domain rules in the data model; the Inference Engine intelligently applies these rules at query time. This easily solves a common issue — what one database calls a “Major Account” another calls an “Enterprise Customer.” To fix, simply write a rule that states both are subclasses of “Top Accounts” and query the full range of details on your connected data. The Inference Engine displays all logic for each result, making explainable AI a reality.
Built-in AI and ML
Stardog Voicebox, a knowledge engineer powered by Large Language Models (LLM), simplifies knowledge graph model building and maintenance as well as query writing with plain language instructions from the user. As you build out a knowledge graph and connect to data sources within your company, you enrich the data by finding connections across all sources, creating a human- and machine-understandable output. Stardog’s built-in machine learning offers both similarity search and predictive analytics. Similarity search is an important functionality when coupled with the connected data of a Knowledge Graph, as it can be used for pattern detection and recommendations.
Navigate your data with Explorer
Search and explore your data fabric without specialized knowledge of a graph query language. Capitalize on your unified data and trace the paths between data points. Stardog Explorer works across virtualized data, finding connections across physically disjointed sources. Answer complex questions like “What does the supply chain look like for this batch of troublesome parts?” or “How are these two financial organizations related to these five transactions and these three shadowy political figures?” Find the shortest route between two data points, unearth links between data no matter their degrees of separation, even determine a connection across your inferred data.
Data quality management
Stardog offers constraints to help manage and measure the data quality of your Enterprise Knowledge Graph. Enforce constraints to prevent Stardog from accessing incorrect data, to find inconsistencies across your data silos, or to flag conflicting data. Set a constraint that a ship date for a purchase must be after the purchase date; Stardog validates across your point-of-sale and shipping systems to ensure your data is correct. Stardog supports the open standard SHACL, a declarative language for specifying constraints over RDF graphs.
Based on open standards
Stardog offers first class support of the SPARQL, SPARQL*, and GraphQL query languages for interacting with your Knowledge Graph. At its core, Stardog is built on the RDF open standards of knowledge representation created by W3C, the same standards body that created the Web. This platform of open standards is designed to represent information — and all its complexities — in a machine-understandable way. As a result, your Knowledge Graph will fundamentally enable greater interoperability and exchange of data.
High-performance graph database
Stardog’s platform is underpinned by a highly efficient, robust, and ACID-compliant graph database. Ensure near-real time responses on up to 100 billion data points per installation. Stardog supports concurrent reads and writes and our query optimizer can handle your most complex queries, thanks in part to its state-of-the-art cardinality estimation. Scale limitlessly with virtual edges and inter-cluster optimized query federation for scale-out use cases. This gives the users ability to scale out their data fabric up to 1 trillion triples, all while enjoying sub-second query times and up to a 98% cost savings when compared with traditional approaches.
Stardog makes creating a knowledge graph easy with an end-to-end solution that links data from your data lake or data warehouse into a knowledge graph that feeds your existing BI tools.
Assign permissions by user profile, restrict access to datasets with Named Graphs, and authenticate Stardog users for secure access.
Scale up to 1 trillion triples; we’re also Kubernetes compatible and ACID-compliant.
Get access to our core engineers for support and lean on your dedicated Customer Success rep to take advantage of the newest features.
Deploy Stardog on-premise or in the cloud. Elect for a Managed Service to guarantee uptime and receive end-to-end support.
See how Stardog builds shared meaning and trusted context across your existing stack, connecting data from MDM, data integration, data catalogs, warehouses, and graph databases for analytics and AI enablement.
