TerminusDB is an open-source document graph database that utilizes a Git-like collaboration model for data management, enabling version control and parallel workflows. It addresses the need for efficient data storage and retrieval by connecting JSON documents in a knowledge graph, allowing for complex queries and relationship-focused applications.
Funding
$5.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional database systems often struggle with complex data relationships, version control, and collaborative workflows, hindering the development of knowledge-intensive applications. Managing data changes and understanding data provenance can be challenging, especially in environments requiring audit trails and parallel development efforts.
Solution
TerminusDB is an open-source document graph database that combines the flexibility of JSON document storage with the power of graph relationships and Git-like version control. It allows developers to model complex data domains as interconnected knowledge graphs, enabling efficient querying and reasoning. The system's branching, merging, and revision control features facilitate collaborative data management and provide a complete audit log of changes. TerminusDB's architecture is designed for scalability and portability, making it suitable for both local and distributed deployments.
Target Audience
TerminusDB targets developers and data scientists building knowledge graphs, semantic web applications, and other data-intensive systems that require version control, collaboration, and complex relationship modeling.
Features
- Git-like branching and merging for data, enabling parallel workflows and version control
- Storage of data as human and machine-readable JSON documents
- Graph data model connecting JSON documents in a knowledge graph
- REST and GraphQL APIs for easy integration with existing systems
- Python and JavaScript clients for interacting with the database
- Succinct data structures and delta encoding for efficient storage and scalability
- Flexible schema design with UI and code-based schema migration tools
- Integration with VectorLink for semantic indexing and AI applications