LanceDB vs Turbopuffer: Vector Databases Comparison
Compare LanceDB and Turbopuffer side by side. Both are tools in the Vector Databases category.
The short answer
Choose LanceDB if open-source and fully featured free tier (LanceDB OSS).
Choose Turbopuffer if up to 100x cost reduction compared to traditional vector databases.
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Quick Comparison
| Category | Vector Databases | Vector Databases |
| Website | lancedb.com | turbopuffer.com |
Pros & Cons: LanceDB vs Turbopuffer
- +Open-source and fully featured free tier (LanceDB OSS)
- +Native multimodal support: text, images, videos, audio, point clouds
- +Up to 100x cost savings with disk-based compute-storage separation
- +Zero-copy automatic versioning and time-travel capabilities
- +Seamless transition from local (OSS) to cloud with same SDK
- −Relatively new platform with smaller ecosystem
- −Documentation still evolving compared to mature alternatives
- −Cloud tier pricing may add up with heavy usage
- −Smaller community support compared to established databases
- +Up to 100x cost reduction compared to traditional vector databases
- +Sub-10ms p50 latency with serverless auto-scaling
- +No namespace limits unlike competitors
- +Enterprise compliance (HIPAA, SOC 2, CMEK) on standard plan
- +Trusted by major companies: Notion, Cursor, Linear, PlayerZero
- −$64/month minimum spend makes it less suitable for small experiments
- −Relatively new platform with smaller community
- −Limited documentation compared to more established solutions
- −Object storage architecture may have latency trade-offs for some use cases
How to Choose a Vector Databases Tool
Key criteria to evaluate when comparing Vector Databases solutions:
About LanceDB
LanceDB is an open-source, AI-native multimodal lakehouse designed for billion-scale vector search. Founded in 2022 by Chang She and Lei Xu as part of Y Combinator's Winter 2022 batch, LanceDB is built on the Lance columnar format and combines embedded simplicity with cloud-scale performance. The platform enables users to store, query, and filter vectors, metadata, and multi-modal data (text, images, videos, point clouds, and more) with support for vector similarity search, full-text search, and SQL. LanceDB offers blazing fast hybrid search, filter, and rerank over billions of vectors with compute-storage separation for up to 100x cost savings. The platform includes zero-copy automatic versioning, allowing users to manage versions of data without needing extra infrastructure. LanceDB's disk-based architecture with compute-storage separation enables up to 100x cost savings compared to memory-based solutions while supporting multimodal data. Based in San Francisco with approximately 30 employees, LanceDB hit $2.3M in revenue with a 15-person team in 2024.
About Turbopuffer
Turbopuffer is a serverless vector and full-text search database trusted by leading companies including Notion, Cursor, Linear, and PlayerZero. Founded in 2023 by ex-Shopify engineers Simon Eskildsen and team, Turbopuffer reached $1 million in ARR within a year of launch and now operates profitably with only 22 employees while powering billions of vectors. The platform features serverless architecture with automatic scaling, sub-10ms p50 latency, support for billions of vectors, full-text search, hybrid search, and metadata filtering. TurboPuffer achieves up to 100x cost reduction compared to traditional vector databases by storing data on object storage like S3 at $0.02 per GB instead of in-memory at $2+ per GB. Turbopuffer has no enforced namespace limits and includes enterprise-grade compliance features like HIPAA BAA, SOC 2, and CMEK even on the non-enterprise plan. Query prices have been reduced by up to 94%, making it 10x-100x cheaper than alternatives with usage-based pricing.
What is Vector Databases?
Purpose-built databases for storing, indexing, and querying high-dimensional vector embeddings used in semantic search, RAG, and recommendation systems.
Browse all Vector Databasestools →Frequently Asked Questions
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