Pinecone is a fully managed vector database with zero infrastructure overhead and pay-as-you-go pricing, while Qdrant is an open-source vector database offering complete control, self-hosting flexibility, and lower operational costs for teams with DevOps resources.
Pinecone vs Qdrant — Side-by-side comparison on A Versus B
Fully managed cloud vector database with serverless architecture and enterprise features.
Open-source vector database with flexible deployment options and advanced query filtering.
Deployment Model. Starting Price (Monthly). Setup Time. Vector Dimension Support. Metadata Filtering. GitHub Stars. Data Sovereignty/Privacy
Choose Pinecone if you prioritize speed-to-market, want zero infrastructure management, and don't mind vendor lock-in with pay-as-you-grow pricing. Choose Qdrant if you need cost control at scale, require self-hosting for compliance/privacy, or want the flexibility of open-source software with an optional managed tier.
Pinecone: $0 (free tier limited to 1M vectors) | Qdrant: N/A
Pinecone: 3 (pod, serverless, custom) | Qdrant: N/A
Pinecone: 0 (standalone database) | Qdrant: N/A
Pinecone: Pay-per-usage (storage + queries) | Qdrant: Self-hosted free or managed from $25/mo
Pinecone: $200-400 (managed pricing) | Qdrant: $25-100 (managed cloud)
Pinecone: 5-10 minutes | Qdrant: 20 minutes
Pinecone: ~2,500 stars | Qdrant: 18,000+ stars
Pinecone: No (SaaS only) | Qdrant: Yes (open-source)
Pinecone: Boolean operators, ranges, sparse-dense hybrid | Qdrant: Advanced boolean/range queries
Pinecone: Up to 20,000 dimensions | Qdrant: N/A
Pinecone: No (separate system) | Qdrant: N/A
Pinecone: ~2,500 (closed-source) | Qdrant: N/A
Pinecone: $70 (minimum pod + index) | Qdrant: N/A
Pinecone: 100M+ (unlimited with multi-pod) | Qdrant: N/A
Pinecone: 20,000 | Qdrant: Unlimited (100K+ tested)
Pinecone: <100 ms | Qdrant: <50 ms (self-hosted)
Pinecone: 15-20 (account + API key setup) | Qdrant: N/A
Pinecone: Not public (proprietary) | Qdrant: 28,000+ stars
Pinecone: ~$150-200 (pod + index + compute) | Qdrant: N/A
Pinecone: Metadata filtering only | Qdrant: N/A
Monthly Cost (1M vectors, 1K queries/day)
Pinecone: 5 billion (enterprise) | Qdrant: N/A
Pinecone: 25+ (LangChain, LlamaIndex, OpenAI) | Qdrant: N/A
Pinecone: Limited; JSON export only, subject to egress costs | Qdrant: N/A
Pinecone: $50 (Starter tier minimum) | Qdrant: N/A
Pinecone: 10B+ (unlimited) | Qdrant: N/A
Pinecone: Advanced (AND/OR/NOT) | Qdrant: N/A
Pinecone: 100,000 free vectors | Qdrant: N/A
Pinecone: Limited (SaaS constraints) | Qdrant: N/A
Pinecone: $0 (free tier with limits) | Qdrant: N/A
Pinecone: $84 (Pro plan, 5M vectors) | Qdrant: N/A
Pinecone: 1B+ (distributed) | Qdrant: 1B+
Pinecone: Yes (REST + gRPC) | Qdrant: N/A
Pinecone: Yes (SOC 2 Type II, HIPAA) | Qdrant: N/A
Pinecone: $4.00 + query fees | Qdrant: $0 (self-hosted) or $25 (managed)
Pinecone: 15-30 minutes | Qdrant: 30-120 minutes
Pinecone: SaaS only (managed) | Qdrant: Self-hosted + managed cloud
Pinecone: Yes (dense + BM25) | Qdrant: Yes (dense + sparse)
Pinecone: Proprietary SDK + REST | Qdrant: OpenAI API compatible + REST
Pinecone: Yes, official integration | Qdrant: N/A
Pinecone: 6+ languages (Python, Node.js, Go, Java, Rust, gRPC) | Qdrant: N/A
Pinecone: SOC 2 Type II, HIPAA-ready, GDPR compliant | Qdrant: N/A
Pinecone: 99.99% | Qdrant: Varies by self-hosted setup
Pinecone: Yes (sparse-dense vectors) | Qdrant: N/A
Pinecone: Python, JavaScript, Go, Java, REST API | Qdrant: N/A
Pinecone: <5 minutes | Qdrant: 15-30 minutes
Pinecone: 99.95% | Qdrant: User-dependent (self-hosted); 99.9% (managed)
Pinecone: Proprietary optimized (HNSW variant) | Qdrant: N/A
Pinecone: Native, advanced filtering on metadata | Qdrant: N/A
Pinecone: None (fully managed) | Qdrant: N/A
Pinecone: 100M+ | Qdrant: Unlimited (billions with clustering)
Pinecone: ~15 minutes | Qdrant: ~20-120 minutes
Cost for 1M Daily Queries + 100GB Storage/Month
Pinecone: $500-800 | Qdrant: $0 (self-hosted); $400-600 (managed)
Pinecone: 20,000 dimensions | Qdrant: Unlimited (limited by memory)
Pinecone: N/A | Qdrant: 1 (vectors only)
Query Latency (1M vectors, single query)
Pinecone: N/A | Qdrant: Python, JavaScript, Go, Java, Rust, C++, .NET
Pinecone: N/A | Qdrant: AGPL-3.0 (with commercial license)
Pinecone: N/A | Qdrant: Yes; Helm charts, StatefulSet support
Pinecone: N/A | Qdrant: Nested fields, range, AND/OR/NOT, geo-spatial
Pinecone: N/A | Qdrant: 15-20 minutes (with Docker)
Pinecone: N/A | Qdrant: Complex nested, geo, range, and boolean queries
Pinecone: N/A | Qdrant: HNSW, IVF-Flat, Product Quantization
Pinecone: N/A | Qdrant: Python, JavaScript, TypeScript, Go, Rust, Java, .NET
Pinecone: N/A | Qdrant: BUSL-1.1 + Cloud/Enterprise
Pinecone: N/A | Qdrant: Yes (BM25 included)
Pinecone: N/A | Qdrant: Full RBAC + OAuth2
How to choose between Pinecone and Qdrant
Pinecone vs Qdrant — Structured Comparison Data
Machine-readable comparison dataset for Pinecone vs Qdrant. Contains 125 attribute comparisons, 5 FAQ pairs.
Pinecone vs Qdrant — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Pinecone vs Qdrant.
Which is cheaper for small projects with < 1GB vectors?
Qdrant is substantially cheaper. Pinecone's free tier covers testing but costs $0.40-1.00 per 1M vectors monthly. Qdrant's self-hosted option is completely free, and the managed tier starts at $25/month regardless of data size for small workloads.
Yes, migration is possible but requires manual work. Both use standard vector formats, but Pinecone's proprietary indexing and metadata structures mean you'll need to re-index vectors in Qdrant. Migration tools are available from community projects, but expect 2-4 weeks for large datasets (1TB+).
Which handles complex metadata filtering better?
Qdrant offers superior metadata filtering with support for complex boolean operators, range queries, and nested filters. Pinecone's payload filtering is simpler and works for basic use cases but lacks the advanced query capabilities needed for complex AI retrieval pipelines.
What if I need HIPAA or SOC 2 compliance?
Qdrant self-hosting gives you complete control for compliance. Pinecone offers SOC 2 Type II certification and HIPAA business associate agreements on enterprise plans, making it viable for healthcare. However, self-hosted Qdrant is often preferred by enterprises requiring data residency in specific regions.
How do they compare for RAG (Retrieval-Augmented Generation) applications?
Both work well for RAG. Pinecone has tighter integrations with LangChain and OpenAI for plug-and-play RAG pipelines. Qdrant offers more flexibility in building custom RAG systems with advanced filtering, making it better for complex multi-stage retrieval workflows. Choice depends on whether you prioritize speed (Pinecone) or customization (Qdrant).
How to Choose Between Pinecone and Qdrant
Deployment Model: Pinecone has Fully managed SaaS only, while Qdrant has Open-source + managed cloud option.
Starting Price (Monthly): Pinecone has $0 (starter), scales to $100+, while Qdrant has $0 (self-hosted), $25+ (managed cloud).
Setup Time: Pinecone has < 5 minutes, while Qdrant has 5 minutes (managed) to 2-4 hours (self-hosted).
Vector Dimension Support: Pinecone has Unlimited, while Qdrant has Up to 65,536 dimensions.
Metadata Filtering: Pinecone has Basic filtering with payload support, while Qdrant has Advanced filtering with complex queries.
GitHub Stars: Pinecone has ~2,500 stars, while Qdrant has ~18,000+ stars.
Data Sovereignty/Privacy: Pinecone has Hosted on Pinecone servers, while Qdrant has Full control with self-hosting option.