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Pinecone vs Qdrant
Trust Score comparison · March 2026
Signal Comparison
680k / wkPyPI downloads180k / wk
38 commitsCommits (90d)200 commits
2.1k ★GitHub stars21k ★
1.2k q'sStack Overflow2k q's
MediumCommunityGrowing fast
PineconeQdrant
Key Differences
| Factor | Pinecone | Qdrant |
|---|---|---|
| License | Proprietary | Apache-2.0 |
| Language | Python / TypeScript | TypeScript / Python / Rust |
| Hosted | Yes | Self-hosted |
| Free tier | — | — |
| Open Source | — | — |
| TypeScript | ✓ | ✓ |
Pick Pinecone if…
- You want a managed vector DB with zero ops overhead
- You're building RAG and need fast semantic search
- You need serverless scaling with pay-per-use pricing
Pick Qdrant if…
- Performance-critical vector search at scale
- You want the fastest self-hostable vector DB
- Memory-efficient workloads with millions of vectors
Side-by-side Quick Start
Pinecone
from pinecone import Pinecone
pc = Pinecone(api_key=os.environ['PINECONE_API_KEY'])
index = pc.Index('my-index')
index.upsert(vectors=[{
'id': 'doc-1',
'values': embedding,
'metadata': { 'text': 'Source document text' },
}])
results = index.query(
vector=query_embedding, top_k=5, include_metadata=True
)Qdrant
import { QdrantClient } from '@qdrant/js-client-rest';
const client = new QdrantClient({ url: process.env.QDRANT_URL, apiKey: process.env.QDRANT_API_KEY });
const results = await client.search('my_collection', {
vector: [0.1, 0.2, 0.3, ...],
limit: 5,
});
console.log(results);Community Verdict
Based on upvoted notes🏆
Qdrant wins this comparison
Trust Score 88 vs 64 · 24-point difference
Qdrant leads on Trust Score with stronger signal data across downloads and community health. That said, the other tool is worth considering if your use case matches its specific strengths above.