Vetted Recommended

Qdrant

Best default vector database for most teams building retrieval and search.

“Best default vector database for most teams building retrieval and search.”

Best default vector database for most teams building retrieval and search.

Why teams pick it

  • First-class LangChain vector store integration with full metadata filtering support.
  • Native LlamaIndex vector store with managed index and retriever abstractions.
  • 1536 and 3072-dim OpenAI embeddings work natively. No adapter needed.
  • Works via LangChain or direct REST integration in serverless functions.

Where it gives ground

  • Self-hosted Qdrant behind a cold-starting container can add latency to the first query.
  • Extremely high-cardinality payload filters can slow down queries if not indexed properly.

What the commercial model looks like

Self-Hosted

$0 /mo

  • vectors: unlimited
  • clustering: true
  • collections: unlimited
  • support_sla: community

Cloud Starter

$25 /mo

  • ram_gb: 1
  • clusters: 3
  • snapshots: true
  • storage_gb: 4
  • support_sla: standard

Enterprise

$500 /mo

  • support: Priority
  • seats: Unlimited

Where this tool shows up

The practical snapshot

Docs quality
9.0
Quickstart
5 min
Starts at
$0