vs

Pinecone vs Qdrant

Pinecone: Fully managed serverless vector database with built-in embedding, reranking and assistants. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud.

key differences

  • Licensing: Pinecone is proprietary (Proprietary SaaS); Qdrant is open source (permissive) (Apache License 2.0).
  • Only Pinecone has encryption at rest.
  • Only Qdrant has full-text search, geospatial, compression.
  • Pinecone has a serverless option; Qdrant does not.

choose pinecone for

  • +RAG over company documents
  • +Semantic search in SaaS products
  • +Recommendation and similarity lookups
  • +Multi-tenant AI apps with per-customer namespaces

best at · Vector search, RAG

choose qdrant for

  • +RAG retrieval with metadata filtering
  • +Recommendation and similarity search
  • +Image and multimodal search
  • +Multi-tenant semantic search

best at · Vector search, RAG

overview
Primary model
Vector
Vector
Also supports
–
Document
Type
Managed service
Database engine
Status
Active
Active
Developer
Pinecone Systems, Inc.
Qdrant Solutions GmbH
First release
2021
2021
Latest version
–
1.20.0 (Oct 22, 2026)
License
ProprietaryProprietary SaaS
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
15.5
35.9
Rank
#213
#55
GitHub stars
–
35.3K
Stack Overflow questions
116
60
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
None
None
Consistency
Eventual
Tunable, Eventual
Schema
Schemaless
Schemaless
Architecture
Serverless, Distributed, Shared storage
Distributed, Client server
deployment
Self-hosted
—
✓
Vendor-managed cloud
✓
✓
Serverless
✓
—
Embedded
—
—
Edge
—
—
Clouds
AWS, Google Cloud, Azure
AWS, Google Cloud, Azure
capabilities
Transactions
—
—
Joins
—
—
Secondary indexes
✓
✓
Full-text search
—
✓
Vector search
✓
✓
Geospatial
—
✓
JSON
✓
✓
Change data capture
—
—
Triggers
—
—
Stored procedures
—
—
Materialized views
—
—
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
—
✓
Encryption at rest
✓
—
Role-based access
✓
✓
Time travel
—
—
Branching
—
—
Online schema changes
—
—
Streaming ingest
—
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
Pinecone API (metadata filter expressions)
Qdrant Query API (JSON filters)
Client languages
Python, JavaScript, Java, Go, .NET, Rust
Python, JavaScript, Rust, Go, Java, .NET
Best for
Vector search, RAG
Vector search, RAG

Pinecone vs Qdrant: FAQ

What is the difference between Pinecone and Qdrant?

Pinecone: Fully managed serverless vector database with built-in embedding, reranking and assistants. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud. Licensing: Pinecone is proprietary (Proprietary SaaS); Qdrant is open source (permissive) (Apache License 2.0). Only Pinecone has encryption at rest. Only Qdrant has full-text search, geospatial, compression.

When should I choose Pinecone over Qdrant?

Choose Pinecone for RAG over company documents; semantic search in SaaS products; and recommendation and similarity lookups. Choose Qdrant for RAG retrieval with metadata filtering; recommendation and similarity search; and image and multimodal search.

Is Pinecone or Qdrant more popular?

Qdrant ranks #55 on the WhichDB Score (35.9/100) and Pinecone ranks #213 (15.5/100). Popularity is not fit: check the requirements that matter for your project.

Are Pinecone and Qdrant open source?

No. Pinecone is proprietary, closed-source software. Yes. Qdrant is open source. License: Apache License 2.0.