TigerBeetle

Serverless Postgres

Serverless Postgres platform separating storage and compute for branching, autoscaling, read replicas, instant restore, and scale-to-zero workloads. Neon works with standard PostgreSQL clients and ORMs, supports extensions such as pgvector, and sits inside a broader Neon backend platform with Auth, Data API, Functions, Object Storage, and AI Gateway features.

MySQL-compatible serverless database

Relational database platform for MySQL and Postgres with Vitess-backed MySQL scale, PlanetScale Postgres, query insights, deploy-request workflows, and Database Traffic Control. It fits production teams that need managed relational performance, safe schema changes, replicas, and database expertise rather than a simple hobby database.

MCP server for connecting AI assistants to Supabase projects

Supabase MCP is Supabase's Apache-2.0 server for connecting AI assistants to Supabase projects. It can expose database, configuration, and project-management workflows to MCP clients such as Cursor, Claude, and Windsurf, while the official docs emphasize permission and security review before production use, SQL changes, or high-privilege database access.

Database branching for coding agents

Ardent is a Postgres database branching platform built for coding-agent workflows. It creates isolated database copies in seconds so Claude Code, Codex, Cursor, or human developers can test migrations, clean data, reproduce bugs, and run risky experiments without touching production. The strongest fit is teams already using Postgres who need agent-safe dev/test databases rather than another generic serverless database.

High-recall Postgres vector search at billion scale

VectorChord is a Postgres extension from the supervc-stack/VectorChord project that brings high-recall vector search to PostgreSQL. As the spiritual successor to pgvecto.rs, it combines IVF indexes with RaBitQ quantization to deliver Pinecone-class performance at billion-vector scale while keeping all data inside a single Postgres database — no separate vector store, no two-system sync, no rewrites when the workload grows.

AI-native database for hybrid RAG retrieval

Infinity is an AI-native database from InfiniFlow that unifies dense vectors, sparse vectors, tensors, and full-text search in a single engine. Built for retrieval-augmented generation (RAG) at scale, it powers hybrid search workflows where lexical matching, semantic similarity, and reranking all happen against one storage layer instead of four loosely coupled services.

Vector search extension for SQLite that runs anywhere

sqlite-vec is a lightweight vector search extension for SQLite written in pure C with zero dependencies. It brings nearest-neighbor search capabilities directly into SQLite databases, enabling AI applications to store and query embeddings without running a separate vector database. The extension works everywhere SQLite runs including Linux, macOS, Windows, WebAssembly in browsers, and even Raspberry Pi devices. Sponsored by Mozilla Builders, Fly.io, and Turso.

Enterprise RAG framework by Tencent

WeKnora is a Tencent-developed LLM-powered knowledge management and Q&A framework for enterprise document understanding and semantic retrieval. Supports 10+ document formats including PDF, Word, Excel, and images with seamless IM platform integration for WeCom, Feishu, Slack, and Telegram. Offers Quick Q&A mode using RAG pipelines and Intelligent Reasoning mode with ReACT agents for complex multi-step reasoning tasks across organizational knowledge bases.