
Turbopuffer
UnclaimedServerless vector and full-text search engine built on object storage for AI applications.
Visit WebsiteThe Bottom Line
Entry price
Paid plans only
Biggest pro
Significantly reduces operational costs compared to traditional vector databases.
Biggest con
Requires a minimum monthly commitment for all pricing tiers.
TL;DR - Turbopuffer
- Serverless vector and full-text search database.
- Built on object storage for 10x cost savings and extreme scalability.
- Achieves sub-10ms p50 latency for billions of vectors.
What is Turbopuffer?
Pros & Cons
Pros
- Significantly reduces operational costs compared to traditional vector databases.
- Handles massive scale with 2.5T+ documents and 10M+ writes/s in production.
- Provides extremely low latency search results, even for large datasets.
- Offers robust security and compliance features including SOC2, GDPR, and HIPAA readiness.
Cons
- Requires a minimum monthly commitment for all pricing tiers.
- Specific details on data migration tools from other databases are not explicitly detailed.
- The 'Launch' plan does not include HIPAA readiness or SSO.
Preview
Key Features
Pricing Plans
Pricing checked Jun 10, 2026
launch
$64 / month
Everything in all plans.
scale
$256 / month
Everything in all plans, plus:
- HIPAA-ready BAA
- Single Sign-On (SSO)
- Private Slack Channel
- Support Hours 8-5
enterprise
Contact us
Everything in all plans, plus:
- Single-Tenancy
- BYOC
- HIPAA-ready BAA
- Single Sign-On (SSO)
- CMEK (Per Namespace)
- Private Networking
- Private Slack Channel
- Support Hours 24/7
Included in all plans
- All database features
- Multi-Tenancy
- SOC2 report, GDPR-ready DPA
- Community Slack & Email
Reviews

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Turbopuffer FAQ
How does Turbopuffer achieve cost savings compared to other vector databases?
Which teams would benefit most from using Turbopuffer?
How does Turbopuffer compare to Pinecone regarding its architecture?
What kind of scalability does Turbopuffer offer for AI applications?
Does Turbopuffer include a free tier for new users?
What are the limitations of Turbopuffer's 'Launch' plan?
Can Turbopuffer handle production workloads requiring high data throughput?
Source: turbopuffer.com