When should I pick Pinecone over turbopuffer?

Pick Pinecone if: You want a hosted index with nothing to operate.

When should I pick turbopuffer over Pinecone?

Pick turbopuffer if: You want a hosted index with nothing to operate.

Which is cheaper, Pinecone or turbopuffer?

At vectors stored 1 million vectors, queries 1 million queries, vectors written or updated 500k writes: Pinecone $113/mo (Standard), turbopuffer $21/mo (Launch), at list prices.

Which do more makers use for vector database?

Among makers' products we track: Pinecone 55, turbopuffer 8.

How do Pinecone and turbopuffer compare in cost as you grow?

At 100k vectors Pinecone costs less ($0 vs $17); from about 500k vectors turbopuffer does ($19 vs $20). Cheapest usable plan at each scale, at list prices.

Pinecone vs turbopuffer

Two managed vector store options for vector database. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.

PineconeManaged vector storellms.txt

turbopufferManaged vector storellms.txt

Ask your AI about this, with this page as the source:ChatGPT ↗Claude ↗Perplexity ↗

Which fits you

Choose Pinecone if

You want a hosted index with nothing to operate

Use it whenYou want vector search without running any infrastructure.

Trade-offClosed source and cloud-only, so leaving means re-indexing somewhere else.

Choose turbopuffer if

You want a hosted index with nothing to operate

Use it whenYou have many separate namespaces, such as one index per customer.

Trade-offNo free tier (paid plans have a monthly minimum), and it's cloud-only.

At a glance

	Pinecone	turbopuffer
Used by	55 makers' products · 23 open-source projects	8 makers' products · 7 open-source projects
Cost at default usagevectors stored 1 million vectors, queries 1 million queries, vectors written or updated 500k writes	$113/mo Standard	$21/mo Launch
Downloads	822.6k/wk−35% vs npm	1.1M/wk3.9× vs npm
Pricing	Free Starter tier; Builder $20/month flat, Standard usage-based with a $50/month minimum, plus an Enterprise tier. · paid from $20/mo	Usage-based tiers with a monthly minimum; higher tiers add SSO, audit logs, and enterprise/BYOC deployments. · paid from $16/mo minimum usage
Free tier	Yes	No
Open source	No	No
Incidents, 90 daysfrom its status page	9 (6 major)	4 (4 major)

Cost as you grow

At 100k vectors Pinecone costs less ($0 vs $17); from about 500k vectors turbopuffer does ($19 vs $20).

turbopuffer Pineconex: vectors stored (1,536 dimensions, about 6 gb per million) (million vectors), other usage scaled with it · cheapest usable plan at each point, list prices · try your own numbers

The numbers, plan by plan

Vectors stored (1,536 dimensions, about 6 GB per million)	Pinecone	turbopuffer
0.1	$0 Starter	$17 Launch
0.5	$20 Builder	$19 Launch
1	$113 Standard	$21 Launch
5	$2,532 Standard	$179 Launch
10	$9,987 Standard	$430 Launch
50	$246,797 Standard	$3,173 Launch
100	$985,753 Standard	$7,576 Scale

From each vendor's pricing page: Pinecone, turbopuffer.

What makers say

Makers on using it for vector database, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.

On Pinecone

TwelveLabs uses Pinecone to efficiently store and search the vector embeddings produced by our embedding model, enabling fast, scalable retrieval across large video and text datasets.

TwelveLabs, the makerSep 2026 ↗

Though we are using function tools to retrieve information from our integrations in real-time, we also use Pinecone to retrieve relevant long-term information.

Tometo, the makerSep 2026 ↗

We needed a vector database that's fast, reliable, and serverless for our RAG system. Pinecone was the easiest to set up and performs consistently at scale.

Starnus, the makerOct 2026 ↗

35 more on the Pinecone page →

On turbopuffer

No maker quote about turbopuffer for vector database yet.

Loved and watch-outs

Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.

Pinecone

Most loved

Getting started is quick, with clear documentation and a generous free tier. PH PH 2 PH 3 PH 4
Handles large vector volumes with low latency as usage grows. PH PH 2
The serverless tier keeps costs down while iterating and at scale. PH PH 2 PH 3

Watch-outs

It is one more database to run and sync, when Postgres or plain search often covers the need. HN HN 2 HN 3 HN 4
Its core features have become a commodity, and it was late to integrated embeddings compared with rivals. HN HN 2 HN 3 HN 4
It stores embeddings without the source chunk, unlike most other vector databases. HN

On Product Hunt: 4.9★, 74 reviews · mentioned most: ease of use, scalability, high-performance vector database

turbopuffer

Most loved

Storing vectors on object storage with a cache in front keeps large-scale search cheap. HN HN 2 HN 3 turbopuffer.com
Handles hundreds of millions to billions of documents, a common next step when pgvector runs out. turbopuffer.com turbopuffer.com 2 turbopuffer.com 3 HN
Operationally simple, with BM25, attribute filtering, recall tuning and consistency options built in. HN HN 2 HN 3 HN 4

Watch-outs

There is no offline local emulator, so development and CI must hit the hosted service. HN HN 2 HN 3
Its paid-only pricing floor is steep for small projects, which often stay on pgvector instead. HN HN 2

Who uses each

Pinecone55 makers' products

Human Behavior InboxAgents

Kick

Kipps AI Kroolo

Kuse +43 more

turbopuffer8 makers' products

Mem0 Playerzero Pylon Readwise

fal Kepler Legora

Linear

What makers pair each with

With Pinecone

With turbopuffer

Transactional Email

Frontend Framework

Database

Neither quite right?

See the whole vector database decision →

pgvectorInside your databaseApps already on Postgres that want vector search in the same database, joined with normal tables.

ChromaEmbedded / local-firstPrototyping RAG on your laptop with a pip or npm install and no server to run.vs Pinecone →vs turbopuffer →

QdrantOpen-source vector storeHeavy metadata filtering alongside vector search, self-hosted from one binary or on its managed cloud.vs Pinecone →vs turbopuffer →

WeaviateOpen-source vector storeHybrid search that mixes keyword and vector results, with built-in modules that can create embeddings for you.vs Pinecone →