Turbopuffer vs Upstash Vector
A side-by-side comparison of Turbopuffer and Upstash Vector, two Vector DB tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Turbopuffer | Upstash Vector |
|---|---|---|
| Category | Vector DB | Vector DB |
| Pricing (differs) | PAID | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment | Cloud | Cloud |
| Platforms (differs) | API | API, Web |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Turbopuffer | Upstash |
| Capabilities (differs) |
|
|
The honest brief
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
Upstash Vector
Pay-per-request serverless pricing and an optional built-in embedding model, so small RAG apps run at near-zero idle cost with no cluster to manage.
- Serverless, pay-per-use pricing
- Simple REST API + Python/TS SDKs
- Optional built-in embedding models
- Metadata filtering on queries
- Free tier to start
- Managed-only; not self-hostable
- Proprietary, not open source
- Fewer index controls than dedicated DBs
When to pick which
Across the signals we compare, Turbopuffer and Upstash Vector differ on pricing and platforms:
- Pricing
- PAID · FREEMIUM
- Platforms
- API · API, Web
Their capability lists differ in recorded depth — compare the full lists above before deciding.