Gel is an object-relational database system that models data as a graph of interconnected objects. By utilizing a strongly typed schema, it enables complex relational queries and polymorphic data structures without the need for traditional join tables. The system integrates native vector storage and similarity search operators, allowing it to function as both a relational and a vector database for semantic data retrieval.
The platform distinguishes itself through a comprehensive suite of developer-centric automation tools. It features a declarative migration system that tracks and versions schema changes, supporting advanced workflows like schema branching and merging. To ensure application-level reliability, the database introspects its own schema to generate type-safe client libraries and query builders, providing consistent data structures across application code.
Beyond core storage, the system provides extensive capabilities for data modeling, including computed properties, custom scalar types, and complex constraints. It supports versatile query execution, ranging from hierarchical nested data retrieval and atomic transactions to integrated retrieval-augmented generation workflows that connect directly to external language models.
The project is managed through a command-line interface that handles the full lifecycle of database instances, including provisioning, monitoring, and automated backup restoration. It offers flexible connectivity options, supporting both native language-specific drivers and a standardized HTTP-based query protocol.
