Quickwit
by Quickwit · Sub-second search and analytics engine on cloud storage
BenchRank score
Screenshots of Quickwit
Homepage
Overview
Quickwit is a search and analytics engine that indexes logs and traces and queries them directly on object storage such as Amazon S3, MinIO or Ceph. Written in Rust on the tantivy library, it decouples compute from storage with stateless indexers and searchers, and exposes a REST API. Indexing is schemaless, with retention and lifecycle policies.
- Best for
- DevOps and data engineers running log and trace search over large volumes on cheap object storage.
- Pricing
- No prices are shown; the site describes Quickwit as open and free community-based software and offers a demo booking, with no published plans.
- Runs on
- Self-hosted
Strengths and trade-offs
Strengths
- Queries data directly on object storage: S3, MinIO or Ceph
- Native OpenTelemetry and Jaeger support for logs and traces
- Runs single or multi-node, on-premise or on Kubernetes
- Retention policies and targeted deletions for GDPR requests
Trade-offs
- Built for low query rates on large volumes, not high-QPS search
- Needs your own object store and queue (S3, Kafka) wired up first
- Site shows no pricing, licence terms or support commitments
- Banner says Quickwit has joined Datadog; future direction unstated
How Quickwit markets itself
A structured read of the promise, proof and page design on Quickwit’s captured homepage.
Homepage capture
“Search more / with less”
- Angle: Outcome / benefit-led
- Hero: Typography only
Pricing
Published plans and prices from Quickwit’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.
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 Quickwit 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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Is this your product?
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