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Amazon S3 Vectors vs Turbopuffer

A side-by-side comparison of Amazon S3 Vectors and Turbopuffer, two Vector DB tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Amazon S3 Vectors

Vector DB

Native vector storage and querying in S3 — serverless, billion-vector scale.

View Amazon S3 Vectors

Turbopuffer

Vector DB

Object-storage-backed vector DB. Serverless economics at scale.

View Turbopuffer

At a glance

Feature comparison of Amazon S3 Vectors and Turbopuffer
AttributeAmazon S3 VectorsTurbopuffer
CategoryVector DBVector DB
PricingPAIDPAID
LicenseProprietaryProprietary
DeploymentCloudCloud
PlatformsAPIAPI
Model supportModel-agnosticModel-agnostic
Vendor (differs)Amazon Web ServicesTurbopuffer

The honest brief

Amazon S3 Vectors

Pay only for storage and queries — AWS claims up to 90% lower cost than dedicated vector DBs for large, infrequently queried indexes.

  • Two billion vectors per index
  • S3 durability and elasticity
  • No idle compute costs
  • Native Bedrock Knowledge Bases integration
  • Locked to the AWS ecosystem
  • Cold queries are sub-second, not low-latency
  • Up to 100 results per query

Turbopuffer

Indexes live on object storage, not RAM, so cost tracks usage not corpus size — built for huge, mostly-cold vector workloads.

  • S3-like billing: cold rest, warm reads
  • Scales to very large, cold corpora
  • No per-namespace minimums
  • Proven at Notion production scale
  • Cold reads have higher latency
  • Paid-only, no free self-host
  • API-only, no managed UI
  • Less mature ecosystem than peers
Amazon S3 Vectors detailsTurbopuffer detailsAll Vector DB apps