Turbopuffer vs Pinecone
A comparison of Turbopuffer and Pinecone built from values read directly from each provider's own documentation, with the source recorded against every figure.
The short answer
- Pick Turbopuffer if
- Teams that want vector search billed like storage rather than compute — object-storage-backed pricing tends to undercut memory-resident vector databases at rest, especially for large, cold datasets.
- Pick Pinecone if
- Teams that want a fully managed vector search product with hybrid search and metadata filtering built in, and don't want to operate the underlying index themselves.
3 sourced criteria separate them:
- Entry paid plan
- Turbopuffer: Launch plan: $16/month minimum usage, including all database features. Scale plan: $256/month minimum. Enterprise: $4,096+/month.
- Pinecone: Builder plan: $20/month flat, for solo developers and small teams. Standard plan is usage-based with a $50/month minimum.
- Pricing model
- Turbopuffer: Subscription with a monthly minimum per tier, plus usage-based overage charges beyond that minimum.
- Pinecone: Usage-based on the Standard plan, with a $50/month minimum before pay-as-you-go charges apply.
- Hybrid search (vector + keyword)
- Turbopuffer: Supported — combines vector search and BM25 full-text search to produce semantically relevant results.
- Pinecone: Supported — combine a keyword signal (BM25 or sparse) with a dense signal at query time, often with reranking.
Pick the criteria you care about. The chart counts how many of them lean toward each provider — the same read as scanning the bars below, just totalled for the ones you chose.
Turbopuffer 0
Pinecone 0
At a glance.
| Criterion | Turbopuffer | Pinecone |
|---|---|---|
| Pricing | ||
| Entry paid plan | Launch plan: $16/month minimum usage, including all database features. Scale plan: $256/month minimum. Enterprise: $4,096+/month. | Builder plan: $20/month flat, for solo developers and small teams. Standard plan is usage-based with a $50/month minimum. |
| Pricing model | Subscription with a monthly minimum per tier, plus usage-based overage charges beyond that minimum. | Usage-based on the Standard plan, with a $50/month minimum before pay-as-you-go charges apply. |
| Vector | ||
| Hybrid search (vector + keyword) | Supported — combines vector search and BM25 full-text search to produce semantically relevant results. | Supported — combine a keyword signal (BM25 or sparse) with a dense signal at query time, often with reranking. |
Where they differ.
Entry paid plan
- Turbopuffer
- Launch plan: $16/month minimum usage, including all database features. Scale plan: $256/month minimum. Enterprise: $4,096+/month.
- Pinecone
- Builder plan: $20/month flat, for solo developers and small teams. Standard plan is usage-based with a $50/month minimum.
Sources (2) →Sources ↓
- Turbopuffer Pricing ↗
“$16/month minimum usage. Includes all database features. [Scale] $256. [Enterprise] $4,096+.”
Read 2026-09-11 · official pricing
- Pinecone Pricing ↗
“$20/month flat, for solo developers and small teams. You'll be charged a minimum of $50/month [on Standard]. Once your usage exceeds this amount, you'll pay as you go.”
Read 2026-09-11 · official pricing
Pricing model
- Turbopuffer
- Subscription with a monthly minimum per tier, plus usage-based overage charges beyond that minimum.
- Pinecone
- Usage-based on the Standard plan, with a $50/month minimum before pay-as-you-go charges apply.
Sources (2) →Sources ↓
- Turbopuffer Pricing ↗
“Minimum monthly commitments ($16 Launch, $256 Scale, $4,096+ Enterprise), plus usage-based overage charges.”
Read 2026-09-11 · official pricing
- Pinecone Pricing ↗
“You'll be charged a minimum of $50/month. Once your usage exceeds this amount, you'll pay as you go.”
Read 2026-09-11 · official pricing
Hybrid search (vector + keyword)
- Turbopuffer
- Supported — combines vector search and BM25 full-text search to produce semantically relevant results.
- Pinecone
- Supported — combine a keyword signal (BM25 or sparse) with a dense signal at query time, often with reranking.
Sources (2) →Sources ↓
- Turbopuffer documentation ↗
“turbopuffer supports vector search and BM25 full-text search. Combining them produces semantically relevant search results.”
Read 2026-09-11 · official docs
- Pinecone documentation ↗
“To get the best of both, use hybrid search — combine a keyword signal (BM25 or sparse) with a dense signal at query time, often with reranking.”
Read 2026-09-11 · official docs
When these numbers change, hear about it. Sources are re-checked monthly; a repricing goes out as a short note.
Which should you choose?
Choose Turbopuffer if…
Teams that want vector search billed like storage rather than compute — object-storage-backed pricing tends to undercut memory-resident vector databases at rest, especially for large, cold datasets.
Editorial · Palash Bagchi · approved
Choose Pinecone if…
Teams that want a fully managed vector search product with hybrid search and metadata filtering built in, and don't want to operate the underlying index themselves.
Editorial · Palash Bagchi · approved
Consider something else if…
- Turbopuffer: The full list of supported similarity metrics matters before committing — that wasn't fully documented in what's sourced here, unlike competitors that publish the complete list.
- Pinecone: Cost predictability at small scale matters more than managed convenience — the $50/month Standard minimum applies before any pay-as-you-go usage starts.
Documented by only one.
These criteria are published by one provider and not the other. An absence here means we have not found a source, not that the feature is missing.
Questions this comparison answers.
Entry paid plan: Turbopuffer or Pinecone?
Turbopuffer: Launch plan: $16/month minimum usage, including all database features. Scale plan: $256/month minimum. Enterprise: $4,096+/month.
Pinecone: Builder plan: $20/month flat, for solo developers and small teams. Standard plan is usage-based with a $50/month minimum.
Should I choose Turbopuffer or Pinecone?
Pick Turbopuffer if Teams that want vector search billed like storage rather than compute — object-storage-backed pricing tends to undercut memory-resident vector databases at rest, especially for large, cold datasets.
Pick Pinecone if Teams that want a fully managed vector search product with hybrid search and metadata filtering built in, and don't want to operate the underlying index themselves.