8 repository-uri
Database systems that combine the strengths of relational storage with graph-based schemas and querying.
Distinct from Relational Databases: None of the candidates specifically capture the hybrid graph-relational identity of the database itself.
Explore 8 awesome GitHub repositories matching data & databases · Graph-Relational Databases. Refine with filters or upvote what's useful.
EdgeDB is a graph-relational database that combines a PostgreSQL backend with a graph-based schema and query language. It functions as an object-relational mapper and graph query engine, allowing data to be modeled as objects and links to align storage with modern programming language structures. The system features a composable query language designed to retrieve deeply nested or interconnected data without the use of manual SQL joins. It includes an integrated AI-driven data retrieval solution with built-in support for vector embeddings. The platform provides a schema migration tool for tr
Combines a relational PostgreSQL backend with a graph-based schema and query language.
Instant is a real-time backend as a service and relational graph database designed to synchronize data across clients automatically. It functions as a data synchronization layer that provides authentication, permissions, and relational data storage for web and mobile applications. The platform includes an optimistic UI framework that updates local interfaces immediately during writes and handles automatic server rollbacks. It also features a real-time presence system to broadcast transient user states, such as cursor positions and online status, to other connected clients. The system manages
Implements a relational graph database that synchronizes structured data across clients in real time.
CodeQL is a semantic code analysis engine and vulnerability scanning tool that treats source code as data. It utilizes a static analysis query language to define complex patterns and security vulnerabilities within a code graph database. The system represents source code as a relational database, enabling the execution of structural queries and data flow analysis. This approach allows for the detection of security flaws and coding errors across large-scale repositories. The tool provides capabilities for automated code auditing, static analysis security testing, and custom vulnerability dete
Represents source code as a hybrid graph-relational database to enable complex structural and data flow analysis.
TypeDB este o bază de date graf și un sistem de gestionare a cunoștințelor (knowledge graph) puternic tipizat. Servește ca un magazin de date multi-model care unifică structurile relaționale, document și graf într-un singur mediu, funcționând atât ca o bază de date conformă ACID, cât și ca un motor de interogare declarativ. Sistemul se distinge prin utilizarea modelării n-ary hypergraph și a ierarhiilor de tip polimorfice. Utilizează o schemă puternic tipizată pentru a impune reguli structurale și a valida integritatea datelor, permițând inferența polimorfică bazată pe tip și polimorfismul de interfață bazat pe roluri pentru a rezolva automat relațiile complexe în timpul execuției interogărilor. Platforma acoperă o gamă largă de capabilități, inclusiv calcularea relațiilor recursive prin tabling, tranzacții cu izolare de snapshot și regăsirea declarativă a datelor. De asemenea, suportă disponibilitatea ridicată prin replicarea clusterelor bazată pe consens, controlul accesului bazat pe roluri și integrarea cu agenți AI pentru regăsirea datelor structurate. Gestionarea este susținută printr-o interfață de linie de comandă, iar sistemul oferă instrumente pentru vizualizarea schemelor graf și auditarea activității administrative.
Functions as a strongly-typed graph database that validates all data and queries against a strictly enforced schema.
Apache AGE is a graph database extension for PostgreSQL that adds openCypher graph query capabilities directly within the relational database environment. It functions as a loadable extension that translates Cypher graph traversal queries into SQL expressions, enabling users to run pattern matching and path analysis alongside standard SQL operations within a single database instance. The extension stores labeled, directed property graphs as isolated schemas with internal relational tables for vertices, edges, and labels, preventing cross-graph interference. It supports hybrid query execution
Adds graph database capabilities to PostgreSQL, enabling hybrid queries with both SQL and Cypher.
FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge graph construction tool and a GraphRAG knowledge store, integrating structured property graphs with vector search to provide grounded context for large language models. The engine is designed as a multi-tenant graph engine, capable of hosting thousands of isolated datasets within a single instance. The system distinguishes itself by using linear algebra for query execution, treating relationship tensors as matrix multiplications to achieve low-latency multi-hop traversals. It ut
Combines row-based precision for metadata access with columnar efficiency for high-performance analytics.
LogonTracer is a security auditing tool designed for logon analysis and forensic log auditing. It functions as a dockerized security auditor that utilizes a security event graph database to map account names and network addresses, allowing for the visualization of complex system compromise patterns and authentication paths. The system features a Sigma detection engine that scans imported event logs against standardized rule sets to identify known malicious activity. It also includes an anomalous behavior detector that applies statistical analysis, graph algorithms, and hidden Markov models to
Maps account and network data into a graph database to analyze complex authentication paths.
Simple Graph este un motor de bază de date de tip graf ușor care utilizează SQLite pentru a persista noduri și muchii. Funcționează ca un motor de graf relațional prin maparea structurilor de graf în tabele standard de bază de date, permițând stocarea atât a datelor structurate, cât și a informațiilor flexibile, fără schemă, prin embedding de documente JSON. Sistemul oferă un utilitar pentru efectuarea de traversări complexe de grafuri și descoperirea de căi prin utilizarea expresiilor tabelare comune recursive. Această abordare permite explorarea conexiunilor profunde și a secvențelor de noduri conectate în rețeaua de date stocată. Proiectul suportă operațiuni standard de gestionare a datelor, inclusiv crearea, actualizarea și ștergerea înregistrărilor de graf. Toate interacțiunile sunt gestionate prin execuția de instrucțiuni pregătite (prepared statements) pentru a asigura manipularea consistentă și securizată a datelor în stocarea relațională subiacentă.
Maps graph nodes and edges into structured relational tables for persistent storage.