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TerminusDB
An open-source, model-driven graph database designed for knowledge-intensive applications.
What it does
Provides a model-driven graph database for storing complex relational data. Features 'Git-like' version control (branch, merge, commit) for data management. Implements GraphQL and WOQL (Web Object Query Language) for flexible data retrieval. Includes 'TerminusCMS', a self-serve content and data platform built on the DB. Offers advanced VectorLink integration for building RAG (Retrieval-Augmented Generation) AI apps.
Why it works
Fidelity: Model-driven approach ensures data always matches its schema, preventing 'data swamps'. Auditability: Version control provides a perfect history of data changes, essential for compliance. Interoperability: Uses JSON-LD and standard web protocols for easy data sharing. Speed to Market: The cloud platform allows developers to build and scale data-heavy apps instantly.
Category: Utilities & System Tools
Team Size: 11-25
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As of 2026
Utilities & System Tools
Revenue: $100k-$1M ARR
An open-source, model-driven graph database designed for knowledge-intensive applications.
Overview
TerminusDB is an advanced open-source graph database and data management platform. It unifies the flexibility of a graph database with the rigorous structure of a version-controlled document store (like Git for data). It allows teams to build complex, knowledge-intensive applications with rich schema verification, making it a critical tool for AI data pipelines, regulatory compliance, and scientific research.
Funding status: Funded
Revenue source: Subscriptions & Managed Services
Customer type: B2B
Pricing: Freemium
Tech stack: Rust, Prolog, React, Node.js, AWS
Platform: Web • Self-hosted
Integrations: GitHub, Google Sheets, Excel, MongoDB, VectorLink, GraphQL
Founder story
Founded in 2019 by Kevin Feeney, Gavin Mendel-Gleason, and Luke Feeney in Dublin, Ireland. Originally started as an EU-funded project (ALIGNED) at Trinity College, the team realized that large organizations were drowning in 'messy data.' They built TerminusDB to bring engineering rigor and structure to the world's most complex data sets.
What it does
- Provides a model-driven graph database for storing complex relational data
- Features 'Git-like' version control (branch, merge, commit) for data management
- Implements GraphQL and WOQL (Web Object Query Language) for flexible data retrieval
- Includes 'TerminusCMS', a self-serve content and data platform built on the DB
- Offers advanced VectorLink integration for building RAG (Retrieval-Augmented Generation) AI apps.
Who it's for
- Data Engineers
- AI/ML Researchers
- Bioinformatics Specialists
- Legal and Financial Analysts
Why it works
- Fidelity: Model-driven approach ensures data always matches its schema, preventing 'data swamps'
- Auditability: Version control provides a perfect history of data changes, essential for compliance
- Interoperability: Uses JSON-LD and standard web protocols for easy data sharing
- Speed to Market: The cloud platform allows developers to build and scale data-heavy apps instantly.
Growth strategies
- Targeted the academic and scientific communities as a spin- out from Trinity College Dublin.
- Used an 'Open- Source First' strategy to build a massive global developer community on GitHub.
- Raised $5.5M in Seed funding to fund the development of their cloud- managed platform.
- Positioned as the 'Knowledge Engine' for the AI era, focusing on data lineage and context.
Alternatives
Comparison overview
- Neo4j: The standard graph DB; TerminusDB is the specialist for Git-like versioning and document-centric graph models.
- SurrealDB: Broad multi-model DB; TerminusDB is more focused on deep schema validation and knowledge graphs.
- TerminusDB is the best choice for teams building high-stakes, data-centric AI applications.