pgvector vs Supabase for real-time apps: Which Should You Use?

pgvector and Supabase solve different problems. pgvector is a PostgreSQL extension for storing and querying embeddings with operators like <->, <=>, and <#>. Supabase is a backend platform built around Postgres, auth, storage, edge functions, and realtime subscriptions.

For real-time apps, use Supabase as the application layer and pgvector inside Postgres when you need semantic search.

Quick Comparison

When pgvector Wins

• •

  You already run PostgreSQL in production.

  • •If your app data lives in Postgres already, adding pgvector is the cleanest move.
  • •You keep one database, one backup strategy, one security model.
• •

  Your main problem is semantic retrieval.

  • •pgvector gives you native vector columns with vector(1536) or similar dimensions.
  • •You can run queries like:

    SELECT id, content
    FROM documents
    ORDER BY embedding <-> $1
    LIMIT 10;
    

  • •That is exactly what you want for RAG pipelines and similarity lookup.
• •

  You need tight control over indexing and query plans.

  • •ivfflat and hnsw indexes let you tune recall vs latency.
  • •If your team knows Postgres tuning, you can squeeze strong performance out of it.
• •

  You want to avoid platform sprawl.

  • •No separate realtime vendor.
  • •No extra backend abstraction layer if your app logic already sits in your API service.

When Supabase Wins

• •

  You are building a real-time product from scratch.

  • •Supabase gives you Auth + Postgres + Realtime + Storage in one stack.
  • •That matters when you need users signing in, rows updating live, files uploaded, and events pushed to clients.
• •

  Your app needs live subscriptions out of the box.

  • •Supabase Realtime can stream database changes over WebSockets.
  • •For chat feeds, task boards, notifications, admin panels, and collaborative editing UIs, that is the shortest path to production.
• •

  You want faster frontend integration.

  • •The supabase-js client gets you CRUD calls quickly.
  • •Row Level Security policies let you expose data safely without building a custom API for every screen.
• •

  Your team wants a managed developer experience.

  • •Dashboard management for tables, policies, auth providers, logs, storage buckets, and edge functions reduces operational drag.
  • •For small teams shipping customer-facing apps quickly, that matters more than database purity.

For real-time apps Specifically

Use Supabase if the app needs live UI updates between users or devices. Use pgvector only as a feature inside that backend when you need semantic matching or recommendations.

The reason is simple: pgvector solves retrieval; Supabase solves product plumbing. Real-time apps need auth sessions, subscriptions via Realtime channels/database changes payloads , file handling ,and policy enforcement before vector search even enters the picture .

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.