Head to head
Pinecone vs Supabase Vector (pgvector)
As a vector database API, Pinecone rates higher on the APIbenchmarks Index, 87.5 to 85.2, a 2.3-point gap. Here is how they compare on each criterion.
Criterion by criterion
| Criterion | Pinecone | Supabase Vector (pgvector) |
|---|---|---|
| Documentation & DX | ||
| Reliability | ||
| Ecosystem & SDKs | ||
| Accessibility | ||
| APIbenchmarks Index | 87.5 | 85.2 |
Specifications
| Pinecone | Supabase Vector (pgvector) | |
|---|---|---|
| Best for | Serverless vector search for production RAG | Postgres-native embeddings, no separate service |
| Free tier | Starter: 2GB storage (~350K vectors), 1 index, no SLA | Free project: 500MB DB, pgvector included |
| Pricing | Per read/write unit + storage | Bundled in Postgres plan (storage-based) |
| Official SDKs | 7 languages | 7 languages |
Is Pinecone better than Supabase Vector (pgvector)?
On the APIbenchmarks Index, Pinecone rates higher (87.5 vs 85.2). 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
Pinecone leads by 2.3 points (87.5 vs 85.2) and wins 2 of 4 criteria; Supabase Vector (pgvector) wins 2.
Winner by criterion
| Criterion | Winner | ||
|---|---|---|---|
| Documentation & DX | 90 | 86 | |
| Reliability | 88 | 80 | |
| Ecosystem & SDKs | 82 | 84 | |
| Accessibility | 90 | 92 |
Choose Pinecone if… / choose Supabase Vector (pgvector) if…
- →documentation & dx matters most to you (90 vs 86)
- →reliability matters most to you (88 vs 80)
- →your use case matches its focus: serverless vector search for production rag
- →ecosystem & sdks matters most to you (84 vs 82)
- →accessibility matters most to you (92 vs 90)
- →your use case matches its focus: postgres-native embeddings, no separate service
Pricing side by side
- Model
- Per read/write unit + storage
- Free tier
- Starter: 2GB storage (~350K vectors), 1 index, no SLA
- Starter$0/month
- Builder$20/month flat
- Standard$50/month minimum usage
- Enterprise$500/month minimum usage
- Bring Your Own Cloud (BYOC)Custom
- 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
Vendor-published pricing, verified 2026-06-27 (Pinecone) and 2026-06-27 (Supabase Vector (pgvector)).
SDK and language coverage
Both · 1
Python
Only Pinecone · 6
TypeScript / Node.jsGoJava.NET / C#REST APIgRPC
Only Supabase Vector (pgvector) · 6
TypeScript / JavaScriptvecs (Python vector client)SwiftKotlinDart / FlutterSQL (native pgvector operators)
Strengths and weaknesses
- +Fully managed serverless architecture eliminates shard/replica/index tuning and ops overhead
- +Low-latency similarity search (sub-10ms p95 on serverless per vendor benchmarks) scaling past 100M+ vectors at 1000+ QPS
- +Clean, consistent SDKs across Python, TypeScript, Go, Java, and .NET with async and gRPC options
- –Consumption-based pricing is hard to predict; multiple reports of bills running 2.5-4x over budget at scale
- –Serverless cold starts add 200-800ms latency on idle indexes and cannot be disabled on that tier
- –Self-hosted alternatives (Qdrant, pgvector, Weaviate) are often dramatically cheaper for steady high-volume workloads
- +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
Pinecone vs Supabase Vector (pgvector): questions
- Which has better documentation, Pinecone or Supabase Vector (pgvector)?
- Pinecone scores higher on documentation and developer experience: 90 vs 86 out of 100.
- Which is more reliable, Pinecone or Supabase Vector (pgvector)?
- Pinecone scores higher on reliability: 88 vs 80 out of 100.
- Do Pinecone and Supabase Vector (pgvector) have a free tier?
- Pinecone: yes (Starter: 2GB storage (~350K vectors), 1 index, no SLA). Supabase Vector (pgvector): yes (Free project: 500MB DB, pgvector included).
- How are Pinecone and Supabase Vector (pgvector) priced?
- Pinecone: Per read/write unit + storage. Supabase Vector (pgvector): Bundled in Postgres plan (storage-based).
- Which has more official SDKs?
- Both list 7 official SDKs.