Redis vs Supabase (pgvector)
Agent-native side-by-side. Scores are curated estimates on a 0–10 scale. Lock-in: higher = worse. Prefer JTBD picks via /api/decide when choosing for a job.
| Dimension | Redis | Supabase (pgvector) |
|---|---|---|
| Overall | 8.1 | 8.6 |
| Capability fit | 8.2 | 8.5 |
| Price / performance | 7.0 | 9.0 |
| Latency / reliability | 9.0 | 8.6 |
| Developer & agent DX | 8.5 | 9.4 |
| Privacy / data retention | 7.5 | 8.0 |
| Lock-in risk (higher = worse) | 4.0 | 3.0 |
| Maturity / track record | 9.6 | 9.0 |
| Pricing | Redis OSS + Redis Cloud; vector search via Redis Query Engine; pay for memory-centric hosting. | Postgres + pgvector + Auth + Storage; usage on compute/storage; free tier. Vectors hitchhike on Postgres. |
| Tagline | Use as agent hot memory/cache, not as your only 100M-vector archive. | Depot default for most agent apps under ~25–50M vectors. Don't add Pinecone until Postgres actually hurts. |
Redis
Use as agent hot memory/cache, not as your only 100M-vector archive. Strengths: Ultra-low latency KV + vectors; Ubiquitous in stacks already; Great session/memory cache for agents.
Strengths
- Ultra-low latency KV + vectors
- Ubiquitous in stacks already
- Great session/memory cache for agents
Weaknesses
- RAM cost at large vector corpora
- Not ideal as sole long-term vector warehouse
- Cluster ops complexity
Supabase (pgvector)
Depot default for most agent apps under ~25–50M vectors. Don't add Pinecone until Postgres actually hurts. Strengths: One backend for auth, DB, storage, vectors; Best DX for many Next.js agent apps; Open standards (Postgres).
Strengths
- One backend for auth, DB, storage, vectors
- Best DX for many Next.js agent apps
- Open standards (Postgres)
Weaknesses
- Vector scale ceiling vs dedicated engines
- Need pgvectorscale/careful indexing past tens of M
- Not a pure vector specialist
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