Vibeleaderboard

Which database should I use for a new AI-built application?

Postgres, unless you have a specific reason not to. It covers relational, JSON, full-text, and vector search in one system, and one database you understand beats three you operate badly.

Surveyed 13 August 2026

Choose data infrastructure

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No.Tool
  1. 01
    PostgreSQL

    Open-source relational database. The most popular open-source SQL database. JSON, full-text search, extensions (pg_vector, PostGIS), and rock-solid reliability.

    Developer Tools
  2. 02
    Supabase

    Open-source Firebase alternative — Postgres database, auth, realtime, storage, and edge functions in one

    Developer Tools
  3. 03
    Neon

    Serverless Postgres with database branching, autoscaling, and instant provisioning

    Developer Tools
  4. 04
    PlanetScale

    Serverless MySQL platform. MySQL-compatible serverless database with branching, non-blocking schema changes, and horizontal scaling powered by Vitess.

    Developer Tools
  5. 05
    Turso

    Edge-hosted SQLite databases. SQLite-compatible database built on libSQL that replicates to edge locations. Ideal for low-latency reads close to users.

    Developer Tools
  6. 06
    MongoDB

    Document database. JSON-document database with flexible schemas. Atlas is the managed cloud offering. Strong fit for fast-iterating apps.

    Developer Tools
  7. 07
    Redis

    In-memory data store. In-memory key-value store used for caching, queues, sessions, and real-time data. Now under the RSALv2/SSPL license.

    Developer Tools
  8. 08
    Upstash

    Serverless Redis and Kafka. Serverless Redis and Kafka with per-request pricing. Ideal for caching, rate limiting, and messaging in serverless architectures.

    Developer Tools
  9. 09
    Pinecone

    Pinecone is a fully-managed, serverless vector database that lets developers store and query embeddings at scale without running infrastructure — a common production retrieval layer for RAG.

    Developer Tools
  10. 10
    SQLite

    Embedded SQL database. Self-contained, serverless, zero-config SQL database in a single file. Public domain and ubiquitous — great for local-first apps, edge, and small services.

    Developer Tools

Ordered by the VibeLeaderboard index, re-surveyed each edition. Something missing?

What to look for

  • 01Can one system cover your access patterns? Every additional store adds operational surface and sync bugs.
  • 02Are migrations versioned in the repository and applied by a pipeline? Dashboard-edited schemas drift silently.
  • 03Does it have a local development story? Testing against production is not a strategy.

Common questions

Do I need a separate vector database?
Usually not. Postgres with pgvector handles millions of embeddings alongside your relational data, which makes filtered semantic queries a single join instead of a cross-system merge.
What is the most common data mistake in AI-built apps?
Schema drift between the repository and production, because a migration was applied in a dashboard and never written down. Version every change as a file and apply it through a pipeline.

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