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Turbopuffer vs Qdrant

Agent-native side-by-side. Scores are curated estimates on a 0–10 scale. Lock-in: higher = worse. Prefer JTBD picks via /api/decide when choosing for a job.

DimensionTurbopufferQdrant
Overall8.28.6
Capability fit8.69.2
Price / performance9.48.8
Latency / reliability8.28.6
Developer & agent DX8.58.4
Privacy / data retention7.88.2
Lock-in risk (higher = worse)4.53.0
Maturity / track record7.08.5
PricingAs of 2026-10-24 (turbopuffer.com/pricing, fetched 2026-10-24): Usage-based with plan minimums: launch '$16/month minimum usage', scale '$256/month minimum usage', enterprise '>= $4,096/month' with '35% usage premium'. '…Rust engine; open-source + Qdrant Cloud; excellent filtered ANN; competitive cloud pricing.
TaglineWhen your vector bill scares you and much of the corpus is cold, Turbopuffer is the interesting answer.Depot pick for serious vector workloads with filters. Self-host or Cloud — either way you can leave.

Turbopuffer

When your vector bill scares you and much of the corpus is cold, Turbopuffer is the interesting answer. Strengths: Excellent cost for large-scale / cold-heavy retrieval; Modern architecture for agent memory at scale; Simple operational model.

Strengths

  • Excellent cost for large-scale / cold-heavy retrieval
  • Modern architecture for agent memory at scale
  • Simple operational model

Weaknesses

  • Younger than Pinecone/Weaviate
  • Feature set narrower for fancy hybrid modules
  • Less community content
GET /api/providers/turbopuffer

Qdrant

Depot pick for serious vector workloads with filters. Self-host or Cloud — either way you can leave. Strengths: Top filtered-search performance; Great self-host story; Cloud option without giving up OSS.

Strengths

  • Top filtered-search performance
  • Great self-host story
  • Cloud option without giving up OSS

Weaknesses

  • Ecosystem slightly smaller than Pinecone mindshare
  • Need to tune HNSW for best results
  • UI/ops polish varying by tier
GET /api/providers/qdrant

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