TopK vs Turbopuffer
A side-by-side comparison of TopK and Turbopuffer, two Vector DB tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
TopK
Vector DBRetrieval engine with hybrid search, multi-vector, and custom ranking in one query.
View TopKAt a glance
| Attribute | TopK | Turbopuffer |
|---|---|---|
| Category | Vector DB | Vector DB |
| Pricing (differs) | FREEMIUM | PAID |
| License | Proprietary | Proprietary |
| Deployment (differs) | Hybrid | Cloud |
| Platforms (differs) | API, CLI | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | TopK | Turbopuffer |
| Capabilities (differs) |
|
|
The honest brief
TopK
One query spans vector, keyword, and multi-vector search with custom ranking — no separate search + vector + reranker stack to stitch together.
- Serverless, no infra to manage
- Runs in your own VPC (BYOC)
- Built-in embedding/OCR inference
- Low latency at billion-doc scale
- SDKs for Python, JS, Rust + MCP
- Newer, smaller ecosystem than peers
- No open-source self-host
- Developer/API-first, no managed UI
- Smaller community vs Pinecone/Qdrant
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
When to pick which
Across the signals we compare, TopK and Turbopuffer differ on pricing, deployment, and platforms:
- Pricing
- FREEMIUM · PAID
- Deployment
- Hybrid · Cloud
- Platforms
- API, CLI · API
Their capability lists differ in recorded depth — compare the full lists above before deciding.