Head to head
Qdrant Cloud vs Supabase Vector (pgvector)
As a vector database API, Supabase Vector (pgvector) rates higher on the APIbenchmarks Index, 85.2 to 82.1, a 3.1-point gap. Here is how they compare on each criterion.
Criterion by criterion
| Criterion | Qdrant Cloud | Supabase Vector (pgvector) |
|---|---|---|
| Documentation & DX | ||
| Reliability | ||
| Ecosystem & SDKs | ||
| Accessibility | ||
| APIbenchmarks Index | 82.1 | 85.2 |
Specifications
| Qdrant Cloud | Supabase Vector (pgvector) | |
|---|---|---|
| Best for | High-performance open-source vector engine | Postgres-native embeddings, no separate service |
| Free tier | 1GB RAM / 4GB disk cluster (~1M vectors), no card | Free project: 500MB DB, pgvector included |
| Pricing | Resource-based (vCPU/RAM/disk) | Bundled in Postgres plan (storage-based) |
| Official SDKs | 8 languages | 7 languages |
Is Qdrant Cloud better than Supabase Vector (pgvector)?
On the APIbenchmarks Index, Supabase Vector (pgvector) rates higher (85.2 vs 82.1). 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 3.1 points (85.2 vs 82.1) and wins 4 of 4 criteria.
Winner by criterion
| Criterion | Winner | ||
|---|---|---|---|
| Documentation & DX | 82 | 86 | |
| Reliability | 78 | 80 | |
| Ecosystem & SDKs | 80 | 84 | |
| Accessibility | 90 | 92 |
Choose Qdrant Cloud if… / choose Supabase Vector (pgvector) if…
- →you need broad SDK coverage (8 official SDKs vs 7)
- →your use case matches its focus: high-performance open-source vector engine
- →documentation & dx matters most to you (86 vs 82)
- →reliability matters most to you (80 vs 78)
- →ecosystem & sdks matters most to you (84 vs 80)
- →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
- Resource-based (vCPU/RAM/disk)
- Free tier
- 1GB RAM / 4GB disk cluster (~1M vectors), no card
- Free Tier$0 (free forever)
- Standard (Managed Cloud)Usage-based (resource billing for vCPU/RAM/disk)
- PremiumCustom / minimum spend required
- Hybrid CloudCustom (pricing on request)
- Private CloudCustom (pricing on request)
- 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 (Qdrant Cloud) and 2026-06-27 (Supabase Vector (pgvector)).
SDK and language coverage
Both · 1
Python (qdrant-client)
Only Qdrant Cloud · 7
JavaScript/TypeScript (@qdrant/js-client-rest)Rust (qdrant-client)Go (go-client)Java (java-client).NET / C# (Qdrant.Client)REST APIgRPC API
Only Supabase Vector (pgvector) · 6
TypeScript / JavaScriptvecs (Python vector client)SwiftKotlinDart / FlutterSQL (native pgvector operators)
Strengths and weaknesses
- +Among the fastest open-source vector engines, Rust core delivers highest RPS and lowest latency in benchmarks vs Weaviate, Milvus, Elasticsearch and Redis
- +Predictable resource-based pricing (pay for vCPU/RAM/disk, not per query), which stays flat regardless of search volume
- +Generous always-free 1GB managed tier with no credit card required
- –Weak built-in vector visualization / observability, the most consistently cited limitation across reviews
- –Learning curve is steep for teams new to vector databases
- –Free clusters are terminated after a period of inactivity (e.g., ~a week unused)
- +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
Qdrant Cloud vs Supabase Vector (pgvector): questions
- Which has better documentation, Qdrant Cloud or Supabase Vector (pgvector)?
- Supabase Vector (pgvector) scores higher on documentation and developer experience: 86 vs 82 out of 100.
- Which is more reliable, Qdrant Cloud or Supabase Vector (pgvector)?
- Supabase Vector (pgvector) scores higher on reliability: 80 vs 78 out of 100.
- Do Qdrant Cloud and Supabase Vector (pgvector) have a free tier?
- Qdrant Cloud: yes (1GB RAM / 4GB disk cluster (~1M vectors), no card). Supabase Vector (pgvector): yes (Free project: 500MB DB, pgvector included).
- How are Qdrant Cloud and Supabase Vector (pgvector) priced?
- Qdrant Cloud: Resource-based (vCPU/RAM/disk). Supabase Vector (pgvector): Bundled in Postgres plan (storage-based).
- Which has more official SDKs?
- Qdrant Cloud lists 8 official SDKs, Supabase Vector (pgvector) lists 7.
Other Vector Database comparisons
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