About Quickwit
Quickwit is a search engine for logs and traces. It keeps the data on object storage and searches it there, which suits large volumes of data.
What it does
Quickwit indexes log and trace data and stores it on cloud object storage such as Amazon S3. Queries run against that storage, so older data stays searchable without being kept on fast disks. The engine is written in Rust and built on the Tantivy search library. It accepts OpenTelemetry and Jaeger data and exposes a REST API.
Key features
- Sub-second search over data kept on object storage
- Schemaless indexing for log records
- OpenTelemetry and Jaeger input
- Retention policies and targeted deletes
- Runs as a single node or as a cluster on Kubernetes
Who it's for
Platform and DevOps teams that handle large volumes of logs and traces and want to control storage costs. Data engineers who need a self-hosted search layer will find it useful too.
Pricing and good to know
The project is open source under the Apache-2.0 license. You run it on your own infrastructure and connect it to object storage such as S3, MinIO or Ceph, and to a queue such as Kafka. It is a backend service, so deployment, scaling and storage planning are your job.
Highlights
- Search logs and traces stored on object storage
- Index records without defining a schema first
- Ingest OpenTelemetry and Jaeger data
- Set retention rules and delete specific records
- Deploy on one node or a Kubernetes cluster
