Head to head
Supabase Vector (pgvector) vs Turbopuffer
As a vector database API, Supabase Vector (pgvector) rates higher on the APIbenchmarks Index, 85.2 to 67.7, a 17.5-point gap. Here is how they compare on each criterion.
Criterion by criterion
| Criterion | Supabase Vector (pgvector) | Turbopuffer |
|---|---|---|
| Documentation & DX | ||
| Reliability | ||
| Ecosystem & SDKs | ||
| Accessibility | ||
| APIbenchmarks Index | 85.2 | 67.7 |
Specifications
| Supabase Vector (pgvector) | Turbopuffer | |
|---|---|---|
| Best for | Postgres-native embeddings, no separate service | Cheap serverless search on object storage |
| Free tier | Free project: 500MB DB, pgvector included | No |
| Pricing | Bundled in Postgres plan (storage-based) | Per GB queried/written + storage |
| Official SDKs | 7 languages | 6 languages |
Is Supabase Vector (pgvector) better than Turbopuffer?
On the APIbenchmarks Index, Supabase Vector (pgvector) rates higher (85.2 vs 67.7). It leads on the four weighted criteria, but price is reported separately, so the best choice still depends on your budget.
Verdict in one line
Supabase Vector (pgvector) leads by 17.5 points (85.2 vs 67.7) and wins 4 of 4 criteria.
Winner by criterion
| Criterion | Winner | ||
|---|---|---|---|
| Documentation & DX | 86 | 74 | |
| Reliability | 80 | 76 | |
| Ecosystem & SDKs | 84 | 58 | |
| Accessibility | 92 | 60 |
Choose Supabase Vector (pgvector) if… / choose Turbopuffer if…
- →documentation & dx matters most to you (86 vs 74)
- →reliability matters most to you (80 vs 76)
- →ecosystem & sdks matters most to you (84 vs 58)
- →accessibility matters most to you (92 vs 60)
- →you want a free tier to start (Free project: 500MB DB, pgvector included)
- →you need broad SDK coverage (7 official SDKs vs 6)
- →your use case matches its focus: postgres-native embeddings, no separate service
- →your use case matches its focus: cheap serverless search on object storage
Pricing side by side
- Model
- Bundled in Postgres plan (storage-based)
- Free tier
- Free project: 500MB DB, pgvector included
- Free$0/mo
- Pro$25/mo per org
- Team$599/mo per org
- EnterpriseCustom
- Model
- Per GB queried/written + storage
- Free tier
- No
- Launch$16/mo minimum
- Scale$256/mo minimum
- Enterprise$4,096+/mo (≈35% usage premium)
Vendor-published pricing, verified 2026-06-27 (Supabase Vector (pgvector)) and 2026-06-27 (Turbopuffer).
SDK and language coverage
Both · 2
TypeScript / JavaScriptPython (supabase-py)
Only Supabase Vector (pgvector) · 5
vecs (Python vector client)SwiftKotlinDart / FlutterSQL (native pgvector operators)
Only Turbopuffer · 4
GoJavaRubyHTTP REST API
Strengths and weaknesses
- +Embeddings live in the same Postgres as relational data, no separate vector service to provision or keep in sync
- +Combine vector similarity with SQL WHERE filters, joins, and row-level security in a single query
- +HNSW indexing (pgvector 0.5.0+) reaches accuracy@10 of 0.99 at 1M vectors and beat Qdrant on equivalent compute in Supabase's benchmarks
- –HNSW index builds are memory-bound and can take hours on a 10M-row, 1536-dim table, producing tens-of-GB indexes
- –Good query latency requires the index to fit in RAM, pushing you to larger, costlier compute add-ons
- –Performance degrades and p99 tail latency grows beyond roughly 5–50M vectors on a single node, not ideal for billion-scale search
- +Object-storage-first architecture cuts storage cost to ~$20-70/TB/month versus ~$1,600/TB/month for RAM-resident incumbents
- +Warm query latency competitive with in-memory engines (~10ms p90 vector, ~18ms p90 BM25 on 1M docs)
- +Native hybrid search: dense + sparse vectors, BM25 full-text, attribute filtering, and regex via trigram indexes
- –High cold-query latency (~444ms p90) when a namespace isn't cached, bad for always-must-be-fast workloads
- –Relatively high write latency (~248ms p90 for 512KB upserts) due to object-storage durability path
- –No free tier and a monthly spend minimum, making pgvector cheaper for small/early projects
Supabase Vector (pgvector) vs Turbopuffer: questions
- Which has better documentation, Supabase Vector (pgvector) or Turbopuffer?
- Supabase Vector (pgvector) scores higher on documentation and developer experience: 86 vs 74 out of 100.
- Which is more reliable, Supabase Vector (pgvector) or Turbopuffer?
- Supabase Vector (pgvector) scores higher on reliability: 80 vs 76 out of 100.
- Do Supabase Vector (pgvector) and Turbopuffer have a free tier?
- Supabase Vector (pgvector): yes (Free project: 500MB DB, pgvector included). Turbopuffer: no free tier.
- How are Supabase Vector (pgvector) and Turbopuffer priced?
- Supabase Vector (pgvector): Bundled in Postgres plan (storage-based). Turbopuffer: Per GB queried/written + storage.
- Which has more official SDKs?
- Supabase Vector (pgvector) lists 7 official SDKs, Turbopuffer lists 6.
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