Supabase基于 PostgreSQL 的开源后端平台，带有认证、存储和实时 API。

4.7 (6)

审阅者 Daniel Nikulshyn·更新 2026年7月

Open Source Backend Database Postgres Vector Search Authentication Developer Tools Self-Hostable

概览

Supabase 是一个开源的 backend-as-a-service，为开发者提供完整的 Postgres 数据库以及构建现代应用所需的工具。它将身份验证、文件存储、即时 REST 与 GraphQL APIs、实时订阅以及 serverless edge functions 集成到一个统一的 managed platform 中。虽然严格来说不是 AI 工具，但 Supabase 因其对 pgvector 的嵌入与相似度搜索支持，已成为 AI 项目中流行的后端选择。团队使用它来存储向量、管理用户数据，并与传统应用功能一起驱动检索增强生成工作流程。开发者可以自行托管整个技术栈，亦可使用托管的云服务，且有 JavaScript、Python、Dart、Swift 等语言的客户端库可供使用。

主要功能

托管的 PostgreSQL 数据库与扩展
内置认证和用户管理
对象存储与访问控制
实时订阅
通过 pgvector 的向量嵌入
边缘函数和自动生成 API

价格

模型: Freemium
分类: 王常服务
评分: 4.7 / 5 (6)

使用场景

RAG Vector Store for AIApps

使用 pgvector 存储和查询嵌入进行检索式生成，结合语义搜索与在一个 PostgreSQL 数据库中管理的相关用户数据。

全栈应用后端

快速使用内置认证、文件存储和自动生成的 REST 和 GraphQL API 部署现代 Web 和移动应用程序，避免编写自定义后端代码。

实时协作功能

使用 WebSocket 备后 Postgres 变更流来实现实时订阅、支持直播仪表板和多用户协作。

自持后端

在您的自身基础设施中部署整个开源 Supabase 栈，以保留对数据的完全控制和避免供应商锁定，同时保持标准 PostgreSQL 兼容性。

优点 & 缺点

优点

完全开源，可自持
基于标准的 PostgreSQL 无锁定
pgvector 支持 AI 和嵌入
富裕的免费套餐用于原型
内置认证、存储和实时

缺点

一些高级功能仍在成熟中
行级安全性有一个学习曲线
边缘函数的冷启动
大规模负载的扩展可能会昂贵

评测

4.7

6 个评分的平均值。

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Elena Rossi

Apr 8, 2026

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on built-in authentication and user management, and fully open source and self-hostable caught me off guard. still, I'd recommend giving it a real trial.

Hiroshi Tanaka

Apr 4, 2026

Solid for our team

We rolled this out across the team last quarter and pgvector support for AI and embeddings. Built-in authentication and user management fits neatly into how we already work, and built-in authentication and user management removed a step we used to do by hand. Cold starts on edge functions, which is the main caveat, but it has held up under daily use.

Sofia Lindqvist

Dec 5, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: managed Postgres database with extensions and fully open source and self-hostable. On balance the feature set — especially vector embeddings via pgvector — justifies the 5 stars for our use case.

Wei Chen

Oct 1, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is vector embeddings via pgvector — handled better than most — and built on standard Postgres with no lock-in. Scaling large workloads can get pricey is my one real gripe. Worth the time if this is your use case.

Mei-Ling Wong

Jul 25, 2025

Use it every day

Honestly didn't expect to like it this much. Vector embeddings via pgvector is exactly what I needed, and generous free tier for prototyping. but I reach for it almost every day now and it just clicks.

Naomi Suzuki

Jun 8, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: realtime subscriptions over websockets and fully open source and self-hostable. On balance the feature set — especially managed Postgres database with extensions — justifies the 5 stars for our use case.