Open-source alternatives to Memgraph

Ragas is an evaluation framework designed to measure the performance of retrieval-augmented generation pipelines and autonomous agent workflows. It provides a comprehensive suite of tools for benchmarking system outputs, utilizing language models as automated judges to score performance against defined rubrics and reference data. By standardizing inputs, retrieved contexts, and generated responses into a unified schema, the project enables consistent analysis across complex AI applications. The framework distinguishes itself through its ability to generate synthetic test datasets from existin

Nebula is a distributed graph database designed for storing and querying massive volumes of interconnected vertices and edges across a horizontally scalable cluster. It functions as a Kubernetes-native database and a distributed graph analytics engine, utilizing a Raft-based distributed store to ensure strong consistency and high availability. The system features an OpenCypher query engine for performing complex graph traversals and pattern matching. It distinguishes itself with a decoupled compute-storage architecture and a shared-nothing distributed design, allowing query processing and dat

H2 is a JDBC-compliant relational database management system written in Java. It functions as an embeddable SQL database that can run directly within an application process to remove network latency, or as an in-memory database for high-performance volatile storage. It also includes a web-based console for executing SQL commands and administering schemas. The system is characterized by its flexible deployment modes, including a standalone server mode for remote TCP/IP access and a mixed mode for simultaneous local and remote connectivity. It features a dialect emulation layer and compatibilit

Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations

SurrealDB is a multi-model database engine designed to store and query document, graph, relational, and vector data within a single ACID-compliant platform. It functions as an AI-native data store, integrating vector search, graph traversal, and machine learning model execution directly into its query layer. By providing a unified declarative query language, the platform eliminates the need for external middleware to synchronize data across different storage models. The platform distinguishes itself through its ability to manage agent memory and complex workflows natively. It allows developer

This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha

Titan is a distributed graph database and computing engine designed for storing and querying massive datasets of interconnected nodes and edges across multi-machine clusters. It functions as a scalable graph storage layer and transactional store, providing a framework for executing large-scale graph processing jobs and deep traversals. The system is distinguished by its pluggable storage backend, which decouples the graph engine from the physical persistence layer. It utilizes vertex-cut data partitioning to balance processing loads and a set-cardinality property model that allows single prop

This project is a multi-model database system designed to store and manage information as documents, graphs, and key-value pairs within a single engine. It functions as a graph database and knowledge graph platform, providing the infrastructure to build, query, and visualize structured data models. By integrating vector search capabilities, the system serves as a vector database that supports retrieval-augmented generation for artificial intelligence applications. The platform distinguishes itself through a unified query language that allows users to perform document lookups, graph traversals

pgdog is a PostgreSQL sharding proxy, distributed SQL router, and connection pooler. It is designed to enable horizontal data distribution by splitting tables and indices across multiple independent servers to scale storage and processing capacity. The project distinguishes itself through online resharding capabilities, using logical replication to move data between shards without application downtime. It supports multiple routing strategies, including hash, list, and range-based query routing, and manages distributed atomic transactions using a two-phase commit process to ensure consistency

Weaviate is a cloud-native vector database and distributed vector store designed to save high-dimensional vectors alongside structured data. It functions as a hybrid search engine that combines vector similarity, keyword matching, and structured metadata filtering within a single query. The system is optimized for retrieval-augmented generation, integrating vector search with generative AI and reranking to power question-and-answer workflows. It distinguishes itself through the ability to merge semantic search with traditional keyword queries and structured metadata filters to improve result

LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters

RedisInsight is a graphical user interface and management tool for browsing, analyzing, and administering Redis databases. It provides a visual environment for exploring key-value data structures, managing database instances, and performing data analysis across different operating systems and deployments. The tool distinguishes itself by providing dedicated visual managers for complex operations, including a vector database manager for configuring embeddings and similarity searches, a query workbench for executing raw commands and Lua scripts, and a performance monitoring dashboard for tracki

NeDB is a JavaScript embedded NoSQL document store designed for Node.js and the browser. It functions as an in-memory data store with the option to persist documents to a local file system, ensuring data survives application restarts. The project utilizes a MongoDB-compatible API to perform data operations, allowing it to serve as a lightweight document indexing system and a persistent file database without requiring a separate database server. Capabilities include querying, inserting, updating, and deleting documents, as well as the ability to create indexes on specific fields to accelerate

Sonic is a high-performance, lightweight search backend designed to provide real-time full-text search and autocomplete capabilities for applications. It functions as a persistent indexing server that maps text terms to object identifiers, allowing developers to integrate rapid search functionality without storing raw document content directly within the search engine. The system distinguishes itself through a specialized graph-based index that enables real-time word prediction and typo correction. Communication is handled via a custom, low-latency binary protocol over raw TCP sockets, which

Graphiti is a backend framework and memory server designed to provide artificial intelligence agents with persistent, time-aware knowledge graph storage. It functions as a memory layer that enables agents to maintain context across long-term interactions by recording and evolving structured data over time. The system distinguishes itself through a specialized temporal graph database that tracks how entities and relationships change using validity windows. By combining semantic vector similarity, keyword matching, and graph topology traversal, the engine performs hybrid retrieval to locate rel

This project is a comprehensive educational resource and curriculum focused on site reliability engineering, distributed systems, and infrastructure operations. It provides technical guides, a systems engineering course, and instructional manuals designed to teach the principles of managing large-scale computing environments. The curriculum covers high-level architectural design for scalability and resilience, including fault-tolerant infrastructure, high-availability patterns, and microservices decomposition. It emphasizes the practical application of site reliability engineering through the

Cognee is an agentic memory management platform designed to provide autonomous agents with long-term semantic recall and structured knowledge. It functions as a framework for building persistent memory systems that connect large language models to graph-based knowledge and vector storage, enabling agents to maintain context across complex tasks and multiple sessions. The platform distinguishes itself through a hybrid approach that combines semantic similarity search with structural graph traversal, allowing for context-aware information retrieval. It features a modular architecture that orche

Dgraph is a distributed graph database designed to store and query highly connected data. It organizes information as nodes and edges to represent complex relationships between entities, providing a platform for managing and analyzing deeply linked datasets. The system functions as a horizontally scalable cluster that partitions data across multiple nodes to maintain performance and availability as information volume increases. It utilizes a specialized query language built for low-latency navigation of interconnected data points, allowing for the execution of complex queries across large-sca

GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without

Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing

LibSQL is a high-performance, distributed SQL database engine that extends SQLite to support remote network access, edge computing, and real-time synchronization. It functions as an embedded database library that integrates directly into application processes while providing the infrastructure to maintain consistency across multiple geographic regions. The platform distinguishes itself by enabling database interaction over standard HTTP protocols, allowing applications to query remote data sources in serverless and edge environments without requiring local filesystem access. It includes nativ

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

Soar is a suite of specialized tools designed for analyzing MySQL performance, advising on indexing, and optimizing SQL syntax. It functions as a performance analyzer, index advisor, and query optimizer to identify bottlenecks and suggest structural improvements for faster execution. The project distinguishes itself through a system for rewriting SQL statements into optimized equivalent versions using custom heuristic rules and patterns. It also features a dedicated index advisor that evaluates query patterns and database metadata to recommend the creation of new indexes. Its broader capabil

This project is a retrieval-augmented generation pipeline designed for building custom ChatGPT plugins that allow language models to query private or professional documents. It implements a full retrieval workflow, from processing and indexing document chunks to retrieving relevant context for natural language queries. The system distinguishes itself through a hybrid retrieval approach that combines dense vector embeddings with sparse keyword matching, further refined by a two-stage semantic re-ranking process. It includes specialized data privacy tools for screening personally identifiable i

AlaSQL is a JavaScript SQL database engine that allows for the filtering, grouping, and joining of in-memory object arrays and JSON data. It functions as an in-memory SQL database and client-side data processor, enabling the execution of SQL statements against JavaScript arrays and external data sources in both browser and server environments. The project serves as a universal data query tool capable of performing relational joins across diverse sources, such as merging Google Spreadsheets, SQLite files, and remote APIs into a single result set. It also acts as an IndexedDB SQL wrapper, allow

JanusGraph is a distributed, elastically scalable graph database designed to store and query highly connected data across a cluster of machines. It supports the property graph data model with ACID consistency and integrates multi-model search capabilities including geo, numeric range, and full-text queries. The database also includes a Graph OLAP engine for running batch analytics and global graph computations on large datasets using the Hadoop framework. The project distinguishes itself through a masterless cluster architecture that eliminates single points of failure, allowing every node to

RavenDB is a multi-model NoSQL document database designed for high-performance, ACID-compliant data storage. It persists structured information as schema-flexible JSON documents and utilizes a unit-of-work session pattern to track entity changes and batch modifications into atomic transactions. The platform is built on a distributed architecture that supports horizontal scaling through sharding and ensures high availability via multi-node, master-to-master cluster replication. The database distinguishes itself through a self-optimizing query engine that automatically creates and maintains ind