Open-source alternatives to MariaDB Server

Databend is a cloud-native data warehouse and OLAP database designed for large-scale analytics. It functions as a SQL-compliant engine and serverless analytics platform that separates compute from storage to allow for independent scaling. The system integrates vector database capabilities, indexing high-dimensional embeddings to enable semantic, hybrid, and full-text searches across massive datasets. It further distinguishes itself through serverless compute management that automatically scales resources based on demand and shuts them down during idle periods. The platform covers a broad set

zvec is an embedded vector database engine and indexing library designed for high-dimensional similarity search. It functions as a hybrid search engine and a retrieval-augmented generation knowledge base, allowing for the storage and retrieval of dense and sparse vectors. The system is distinguished by its hybrid retrieval pipeline, which fuses vector similarity, full-text keyword matching, and scalar metadata filtering into single query operations. It supports a plugin-based model integration system for registering custom embedding models and rerankers, as well as language bindings for nativ

MySQL Server is a relational database management system designed to organize and store structured information. It functions as a comprehensive SQL server platform that provides reliable transactional integrity and high-performance query execution for enterprise data management. The system distinguishes itself through a pluggable storage engine architecture that decouples logical query processing from physical data storage, allowing for specialized handling of diverse workloads. It maintains data consistency and high concurrency through multi-version concurrency control and write-ahead logging

AliSQL is a fork of MySQL by Alibaba that extends the relational database management system with enhancements for high performance, scalability, and enterprise-grade availability. It retains the core MySQL identity as a SQL-based database for storing, organizing, and retrieving structured data, while adding optimizations for large-scale transactional and analytical workloads. The project differentiates itself through a set of Alibaba-specific improvements, including a columnar engine for accelerating analytical queries directly on MySQL tables, and a distributed, shared-nothing NDB Cluster en

YugabyteDB is a distributed SQL database and relational data store designed for horizontal scalability and high availability across multiple nodes or regions. It functions as a cloud-native system that ensures continuous availability and supports PostgreSQL compatible query languages and drivers. The system includes specialized capabilities as a vector database for AI, utilizing high-dimensional indexing to perform similarity searches. It is engineered as a multi-region cloud database that synchronizes data across different geographic locations to maintain global availability. The project co

OceanBase is a distributed SQL database designed for high availability and strong consistency across multiple nodes and regions. It functions as a hybrid transactional and analytical processing engine, allowing real-time analytics and transactions to execute on a single data copy. The system also serves as a vector database engine for indexing and querying vector data to power semantic search and recommendation systems. The platform features native compatibility layers for MySQL and Oracle, enabling the migration of legacy workloads without rewriting SQL code. It utilizes a Paxos-based distri

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

TiDB is a horizontally scalable, distributed SQL database designed to provide consistent transactional storage and high-performance analytical processing within a single unified architecture. It utilizes a decoupled compute-storage design and a distributed key-value storage layer to ensure horizontal scalability and efficient range-based queries. By employing a consensus-based replication algorithm, the system maintains high availability and automatic failover across multiple nodes and geographical regions. The platform distinguishes itself through its hybrid transactional and analytical proc

TurboVec is a high-performance Rust vector database and quantized search index designed for storing and retrieving high-dimensional embeddings. It functions as a pluggable vector store for large language model orchestration frameworks, providing a memory-efficient alternative to standard in-memory storage. The project distinguishes itself through a high-dimensional vector compressor that utilizes random rotation and data-oblivious scalar quantization to reduce memory footprints. Retrieval is accelerated via SIMD kernels that process distance calculations and search operations for increased th

Lance is a versioned columnar data format and storage engine designed as a multimodal AI lakehouse. It serves as a vector database storage engine and a cloud object store dataset manager, organizing images, video, audio, and embeddings into a unified format optimized for machine learning workflows. The project distinguishes itself by combining a columnar layout for structured data with a specialized blob store for large multimodal tensors. It implements a hybrid search engine that integrates vector similarity search, full-text search, and SQL analytics on a single dataset, supported by a stor

Manticoresearch is a high-performance search engine and database designed for indexing and retrieving large datasets. It functions as a full-text search engine, a vector search database, and a SQL-based search database, providing a distributed search cluster architecture. The system provides an alternative to the Elasticsearch stack, offering a compatible API for indexing and searching structured and unstructured data. It distinguishes itself by supporting multiple retrieval methods, including vector matching for similarity search, geospatial queries, and traditional full-text ranking. The p

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

Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and images. It functions as a dataset version control system and a machine learning data streaming engine to support large-scale model training. The system utilizes a serverless PostgreSQL vector store to index high-dimensional embeddings for semantic search. It provides a visual interface for inspecting multimodal datasets and viewing annotations such as bounding boxes and masks. The platform handles cloud-agnostic storage synchronization and implements lazy, compressed data strea

Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr

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

YDB is a distributed SQL database and analytical engine designed for horizontal scalability and strong consistency. It functions as a multi-model system that supports transactional and analytical workloads through a distributed architecture providing serializable ACID transactions. The system is distinguished by its broad protocol compatibility, implementing the PostgreSQL wire protocol for standard SQL drivers and the Kafka protocol for messaging and streaming. It further serves as a vector database, supporting vector indexes and approximate nearest neighbor searches for semantic search and

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

Chroma is a specialized vector database designed to index and retrieve high-dimensional data representations for semantic similarity search. It functions as a comprehensive platform for information retrieval, enabling the storage and management of unstructured documents alongside structured metadata. By mapping data into numerical representations, the system facilitates rapid similarity lookups across large datasets. The platform distinguishes itself through a hybrid search infrastructure that combines dense vector embeddings with sparse keyword and regular expression matching to balance sema

USearch is a high-performance vector similarity search engine and approximate nearest neighbor index designed for dense embeddings. It functions as a low-level vector database core and high-dimensional vector indexer, providing the primitives necessary to store and retrieve vectors across massive datasets. The engine distinguishes itself through hardware-level SIMD acceleration for distance kernels and a proximity-graph indexing system that enables fast retrieval across billions of vectors. It supports multi-precision vector quantization to balance memory usage and accuracy, and utilizes memo

ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

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

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

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

Infinity is a distributed vector database and multimodal vector store designed to manage large-scale datasets for retrieval and similarity search. It serves as a backend for large language model applications and retrieval augmented generation pipelines by storing and retrieving dense vectors, sparse vectors, and full-text data. The system functions as a hybrid search engine, combining vector embeddings and full-text search with reranking algorithms to identify the most relevant documents. It supports multimodal data storage, allowing the maintenance of diverse data types including tensors, st

ScyllaDB is a distributed NoSQL database engine designed for high-throughput data storage and low-latency performance at scale. It functions as a shard-aware platform that manages large-scale datasets across distributed clusters, providing a foundation for real-time applications that require consistent availability and operational stability. The system distinguishes itself through a shared-nothing architecture that distributes data across independent CPU cores to eliminate lock contention. It incorporates a user-space networking stack and an asynchronous event-driven engine to maximize hardwa

This project is a Model Context Protocol server and AI agent database connector. It provides a standardized communication layer that allows language models to interact with relational data stores, read database schemas, and manage PostgreSQL database resources. The implementation acts as a serverless host for the Model Context Protocol, deploying on distributed edge functions to connect AI assistants to a project. This enables AI agents to perform database administration, execute SQL queries, and handle schema migrations through an AI-compatible interface. The system covers broader capabilit

PostgreSQL is an object-relational database management system designed for the persistent storage and retrieval of structured information. It functions as an ACID-compliant database server, utilizing standard query language protocols to maintain data consistency and reliability across large-scale application datasets. The system distinguishes itself through an extensible architecture that allows for the definition of custom data types, operators, and indexing methods. It employs multi-version concurrency control to enable simultaneous read and write operations without blocking, supported by a