Tool dossier

Quickwit

High-performance search engine designed for big data, offering scalability, real-time indexing, and cost-effective operations.

3 sources 11,081 stars Self-hosted Apache-2.0

Product snapshot

How the interface presents itself

Quickwit interface screenshot

Positioning

What this project is really offering

The goal here is to separate raw catalog facts from the sharper product shape users care about before they commit time.

About

Quickwit is a cloud-native, open-source search engine designed for sub-second search and analytics on cloud storage. It offers a robust alternative to traditional search technologies like Datadog, Elasticsearch, Loki, and Tempo, optimized for limitless data volumes with low query per second (QPS) requirements. Built on Rust and Tantivy, Quickwit ensures optimized CPU and processing power, executing queries directly on object storage for improved performance at a fraction of the usual cost. Quickwit stands out with its unique architecture, making it an ideal choice for organizations looking to manage and search through extensive logs and traces efficiently. Its cloud-native design and compatibility with various object storage and distributed queue systems provide flexibility and cost-effectiveness, empowering DevOps and data engineers to achieve more with their data.

Highlights

The capabilities most worth remembering

01

Scalability

02

Real-time indexing

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Cost-effective

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Cloud-native

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Full-text search

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Time-series optimized

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Open-source

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Sub-second Latency

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Decoupled Storage & Compute

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Cloud-native Deployment

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Optimized for Logs and Traces

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Rust-based Architecture

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Enterprise-ready

Evidence

What backs up the editorial summary