cayleygraph/cayley
Cayley
Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model. It functions as an RDF quad store, managing information through subjects, predicates, objects, and labels.
The system features a modular graph store architecture with pluggable backends, allowing it to swap between in-memory storage and various external persistent databases. It includes a GraphQL-inspired API and a dedicated data visualizer for the interactive exploration of nodes and edges.
Query capabilities cover bidirectional path traversal and multi-syntax execution using JSON or GraphQL. The engine supports complex node and result filtering, set operations, and stateful query management to handle large-scale data traversal.
The project provides options for containerized deployment and integration with managed cloud hosting environments.
Features
- Quad Stores - Uses a quad-based data model representing information as subjects, predicates, objects, and graph labels.
- Graph Databases - Provides a complete graph database engine for storing and querying interconnected data using nodes and edges.
- Data Persistence and Storage - Persists interconnected graph data to a durable storage engine with configurable synchronization.
- Graph Traversal Strategies - Enables discovery of connected nodes by following edges in forward, reverse, or bidirectional directions.
- Graph Data Models - Manages complex interconnected data using a relational graph structure based on subjects, predicates, and objects.
- Pluggable Storage Backends - Features a modular architecture with pluggable backends to swap between in-memory and persistent external databases.
- Graph Query Interfaces - Provides a GraphQL-inspired interface to retrieve nodes, properties, and nested relationships from the graph.
- Graph Querying - Provides capabilities for traversing and retrieving connected data using GraphQL-inspired and JSON syntaxes.
- JSON Query Constraints - Allows retrieving nodes and edges by defining constraints in JSON objects using literal matches and subqueries.
- Graph Traversal - Implements bidirectional path traversal to discover complex connections across large-scale networks of nodes.
- Interactive Graph Visualizers - Provides an interactive tool for rendering interconnected nodes and edges visually to explore the graph.
- Graph Traversal Engines - Executes queries by following edges in forward or reverse directions to discover connected nodes through recursive path matching.
- Graph Query Interfaces - Implements a GraphQL-inspired API for retrieving interconnected graph data and nested relationships.
- Graph Pattern Matching - Matches graph patterns in the opposite direction of their definition to find target nodes.
- Query Mapping - Translates JSON objects into internal graph constraints and subqueries to retrieve nodes and edges.
- Graph Node Filtering - Restricts the set of nodes based on predicate-object matches, range constraints, string matching, or identities.
- Multi-Syntax Query Interfaces - Supports running data retrieval tasks using multiple query language options based on syntax preferences.
- Traversal State Management - Saves intermediate nodes or predicates into named tags to branch traversals or return to previous states.
- In-Memory Databases - Includes an in-memory storage engine for high-performance, non-persistent graph operations.
- Pluggable Storage Drivers - Implements a pluggable architecture allowing the storage backend to be swapped between in-memory and persistent databases.
- Query State Management - Allows the execution engine to save intermediate node sets into named tags for branching during traversal.
- Search Result Filtering - Provides mechanisms to restrict returned nodes and properties based on exact property value matches or quad labels.
- Graph Set Operation Engines - Implements union, intersection, and exception operations to combine or subtract graph paths.
- Storage Backend Integrations - Integrates with various external storage providers through a modular backend architecture.
- Relationship Graph Visualizers - Ships a dedicated visualizer for the interactive exploration of nodes and edges within the graph.
- Storage Engine Interfaces - Provides a modular interface that decouples graph query logic from the underlying physical storage implementations.
- Database Tools - Graph database.
- Databases and Storage - A graph database designed for complex, linked data structures.
- Graph Databases - Open-source graph database for linked data.
- Relational Databases - Open-source graph database from Google.
