Open-source alternatives to Bdash

This application is a desktop utility for managing, editing, and visualizing local database files. It provides a graphical interface for executing SQL queries, designing database structures, and performing routine maintenance tasks on data stores. The software distinguishes itself through its support for encrypted database files, allowing users to manage password-protected data using modular cryptographic extensions. It also offers built-in tools for data analysis, enabling the generation of graphical charts and plots directly from query results to identify trends within datasets. Beyond its

Sequel Pro is a native macOS database administration application and graphical user interface client. It provides a dedicated desktop environment for managing MySQL and MariaDB databases, allowing users to perform server configuration and organize database data. The tool focuses on relational database visualization and the administration of both MySQL and MariaDB server instances. It enables the organization of data and the execution of management tasks through a desktop interface designed for macOS.

Sequel Ace is a native macOS application that serves as a management client for MySQL and MariaDB database instances. It provides a graphical user interface for executing SQL queries and administering database structures without the use of a command line. The project enables the visualization of relational database structures and records in a visual format. It includes a visual query editor and data browser for writing and executing SQL statements to retrieve or modify data. The application handles database administration tasks and data storage through a native desktop interface. It manages

Medis is a native macOS desktop application that serves as a Redis client for connecting to local and remote instances. It provides a graphical user interface for visualizing, editing, and managing data stored within Redis key-value stores. The application includes a visual key-value explorer for browsing records and a dedicated terminal console for executing raw instructions and system shell commands. It supports secure remote administration through SSL encrypted connections and the use of host, port, and password credentials. Connection management is handled via profiles that allow saving

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

MCP server for interacting with Neon Management API and databases

This project is a cross-platform desktop application that provides a graphical interface for managing and interacting with Redis databases. Built as a standalone software program, it functions as a centralized connection manager that allows users to visualize data structures, perform administrative tasks, and inspect records across multiple database environments. The application distinguishes itself through its integration with external processes and command-line workflows. Users can define custom viewers to render specific data formats using external tools and launch the interface directly f

An official Qdrant Model Context Protocol (MCP) server implementation

The official Redis MCP Server is a natural language interface designed for agentic applications to manage and search data in Redis efficiently

RedisDesktopManager is a NoSQL database manager and graphical user interface client for Redis. It serves as a desktop administrator for monitoring keys, managing memory, and executing commands on Redis servers. The application provides a visual environment for Redis data visualization, cache inspection, and database administration. It allows for the organization and editing of records across multiple data stores and server instances without the use of a command-line tool.

A Model Context Protocol Server for MongoDB

Database CRUD Application Built on Electron | MySQL, Postgres, SQLite

A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities

nocodb mcp server

FastoRedis is a crossplatform Redis GUI management tool.

🍃🔎 MongoDB Lens: Full Featured MCP Server for MongoDB Databases

🗂️🤖 Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases

A Model Context Protocol (MCP) server implementation that provides database interaction with Snowflake. This server enables running SQL queries via tools and exposes data insights and schema context as resources.

A Model Context Protocol (MCP) server that provides secure, read-only access to BigQuery datasets. Enables Large Language Models (LLMs) to safely query and analyze data through a standardized interface.

Neo4j is a native graph database management system designed to store and query highly connected data using a property-graph model. It provides an ACID-compliant transaction engine that ensures data integrity, supported by a distributed cluster architecture that maintains causal consistency across nodes. Users interact with the system through a declarative query language, which allows for complex pattern matching and path traversal without requiring manual traversal logic. The platform distinguishes itself through its hybrid approach to data retrieval, combining traditional graph-based queries

mcp server for tidb

MCP Server to interact with data in Couchbase Clusters

FastoNoSQL is a crossplatform Redis, Memcached, SSDB, LevelDB, RocksDB, UnQLite, LMDB, ForestDB, Pika, Dynomite, KeyDB GUI management tool.

A Model Context Protocol server that provides access to BigQuery

Bigcache is a thread-safe, in-memory key-value store for Go designed to minimize garbage collection pauses. It functions as a memory-optimized cache capable of storing gigabytes of data while maintaining low latency during high-volume operations. The system avoids garbage collection overhead by managing memory through large byte arrays and manual allocation. It utilizes a circular-buffer layout to reuse space and lock-striped sharding to reduce contention during concurrent read and write access. The project provides capabilities for high-volume in-memory caching and low-latency data retrieva