
Databend
by Databend · Open-source Rust data warehouse for SQL, search and vector workloads
BenchRank score
Screenshots of Databend
Homepage
Overview
Databend is an open-source, Rust-based cloud data warehouse that runs SQL analytics, full-text and JSON search, and vector search on object storage including S3, Azure, GCS, OSS, R2, MinIO and HDFS. A Raft-backed meta service handles metadata and transactions while a vectorised engine queries columnar blocks, segments and snapshots. It is offered as a managed service or self-hosted.
- Best for
- Data teams wanting SQL analytics, full-text and vector search in one warehouse over object storage
- Pricing
- Usage-based: storage at $23.00/TB/month plus compute from $1.00/hour on Personal or $1.50/hour on Business, with HTTP API requests at $1–$2 per 10,000; the Dedicated tier is quoted by sales and the core can be self-hosted.
- Runs on
- WebSelf-hostedCLI
Strengths and trade-offs
Strengths
- Analytics, full-text search and vector search in one SQL engine
- Runs on S3, Azure, GCS, OSS, R2, MinIO or HDFS; self-host via Docker
- SOC 2 Type II, GDPR, RBAC, masking policies and AWS PrivateLink
- Sub-500ms provisioning with per-second warehouse billing
Trade-offs
- Compute, storage and API requests are billed separately, so costs need modelling
- Personal tier keeps only 1 day of history and 1 business day support response
- PrivateLink and sub-15-second provisioning need the Business tier or above
- Dedicated tier prices are hidden and require a sales conversation
How Databend markets itself
A structured read of the promise, proof and page design on Databend’s captured homepage.
Homepage capture
“Data Agent-Ready. One Warehouse.”
- Angle: All-in-one / consolidation
- Hero: Code snippet
Pricing
Published plans and prices from Databend’s own pricing page.
How this score is made up
Each dimension is scored out of 100 and combined into the headline score using fixed weights.
MCP support
Whether an agent can drive the product through the Model Context Protocol, and how much setup that takes.
API quality
Public API surface: machine-readable spec, official SDKs, documented auth, errors, rate limits and versioning.
Documentation
Publicly reachable docs — coverage, freshness, code samples and machine readability.
Agent friendliness
How readable the site is to an automated client: llms.txt, structured data, server-rendered content, crawler access.
Pricing transparency
Whether real prices are published, self-serve signup exists, and usage costs are knowable without a sales call.
Changelog
A public, dated record of what shipped and when — the clearest signal that a product is still alive.
Marketing site structure
Whether the site answers a buyer's questions: clear positioning, the pages that matter, and accessibility.
Page speed
How fast the site loads for real visitors: Chrome UX Report 75th-percentile LCP, INP and CLS, with a Lighthouse mobile run standing in where a site has too little traffic for field data.
Operational trust
Status page and incident history, security disclosure, compliance and data-processing documentation.
Measured, but not part of the score
Useful to know, but not a mark for or against the product — so these do not affect the ranking.
Openness
Source availability, self-hosting, data export and open standards. Scored and shown, but not part of the composite — paid SaaS is not worse for being paid SaaS.
Maintenance
Release cadence and repository activity. Scored and shown, but not part of the composite — it is only measurable for open repositories.
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Where this comes from
The Databend pages BenchRank reads when it scores the product — its documentation, release notes, status and security pages, and its repository where there is one.
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