Vector Database Pricing: Pinecone vs Weaviate vs Qdrant vs pgvector (April 2026)
Embedding generation is a one-time cost. Storage is forever. This page covers the storage formula, the major vector database options at real-world scales, and the dimension-reduction savings nobody mentions.
Storage Cost Calculator
Storage only. Add query/read costs for Pinecone serverless and Qdrant Cloud. Binary encoding requires Titan V2 (AWS) or custom quantization.
The Storage Formula
Each embedding vector is stored as 32-bit floats. The raw storage size before index overhead:
Managed vector databases charge for both the raw vectors and the index. HNSW index adds 20-40% overhead on top of raw vector storage. For pricing purposes, most providers bill for total storage used, including index. The calculator above uses raw vector math; add ~30% for real-world managed DB estimates.
Monthly Storage Cost by Scale
| Scale | Raw size | Pinecone Serverless | Qdrant Cloud | Weaviate Cloud | Zilliz Cloud | pgvector |
|---|---|---|---|---|---|---|
| 1M vectors (1536d) | 5.7 GB | $2/mo | $0.69/mo | $0.54/mo | $0.57/mo | $0.13/mo |
| 10M vectors (1536d) | 57.2 GB | $19/mo | $7/mo | $5/mo | $6/mo | $1/mo |
| 100M vectors (1536d) | 572.2 GB | $189/mo | $69/mo | $54/mo | $57/mo | $13/mo |
Raw float32 storage. Add 20-40% for HNSW index overhead in practice. Query costs not included. Pinecone serverless also charges per read/write operation.
Provider-by-Provider Analysis
Pinecone
$0.33/GB/month (serverless)- + Purpose-built vector DB
- + Generous free tier (100k vectors)
- + Managed indexes, no ops burden
- - Cold start 200ms-2s on serverless
- - Pod-based starts at $70/month minimum
- - More expensive per GB than alternatives
Best for: prototypes and small production apps where ops burden is unacceptable. Serverless cold-start is the main risk for latency-sensitive applications.
Pricing pagepgvector
~$0.023/GB on self-hosted Postgres- + Near-zero marginal cost on existing DB
- + SQL-compatible; standard tooling
- + No extra infrastructure
- - Scales to ~50M vectors before quality degrades
- - HNSW index build time grows with data
- - No built-in filtering at extreme scale
Best for: applications already on Postgres with under 50M vectors. The default choice for small-to-medium RAG applications. Move to a dedicated vector DB at scale.
Pricing pageQdrant
$0.12/GB/month (Qdrant Cloud)- + Strong filtering at scale
- + Open-source self-hosting option
- + Rust-based; fast and memory efficient
- - Less managed tooling than Pinecone
- - Sizing requires RAM+disk understanding
Best for: production RAG at medium scale (5M-500M vectors), especially with metadata filtering requirements. Self-hosting on EC2 is cost-effective at 50M+ vectors.
Pricing pageWeaviate Cloud
$0.095/GB/month- + Lowest managed $/GB of major providers
- + GraphQL and REST APIs
- + BM25+vector hybrid search built-in
- - More complex setup than Pinecone
- - Pricing tiers can be opaque
Best for: hybrid search (keyword + semantic) use cases. The BM25 integration is first-class and often eliminates the need for a separate keyword search layer.
Pricing pageZilliz Cloud (Milvus)
$0.10/GB/month- + Best for billion-scale corpora
- + Open-source Milvus-compatible
- + Strong horizontal scaling
- - Overkill for <10M vectors
- - More operational complexity
Best for: billion-scale document corpora, media libraries, and enterprises with existing Milvus deployments. Comparable pricing to Qdrant with better 1B+ scale story.
Pricing pageDimension Reduction: The Storage Shortcut
For models that support Matryoshka Representation Learning (OpenAI text-embedding-3-large, Google Gemini models), you can request fewer dimensions via the API. Storage cost scales linearly with dimensions:
| Dimensions | GB per 100M vecs | Pinecone cost/mo | Savings vs 3072d |
|---|---|---|---|
| 3072 (full) | 1144.4 GB | $378 | baseline |
| 1536 (half) | 572.2 GB | $189 | $189 saved |
| 768 (quarter) | 286.1 GB | $94 | $283 saved |
For 100M vectors at 100M-scale, halving dimensions saves $189/month on Pinecone with minimal quality impact. MTEB score drop: roughly 1-2 points.