An open-source observability database that stores metrics, logs, and traces in one columnar engine on object storage, queryable with SQL and PromQL.
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What is it?
Parseable is an observability platform built on a data lake architecture. It ingests logs, metrics, traces and events from applications, agents and systems, and stores them in columnar Parquet format on object storage such as S3. Compute is stateless, so storage and processing can scale independently.
The platform bundles alerting, dashboards, anomaly detection, APM, PromQL and SQL querying into one binary, so teams do not need to combine several separate tools for these tasks. Data can arrive through popular logging agents, OpenTelemetry, Kafka, eBPF and other integrations, and OpenTelemetry Collector setups can be pointed at it directly.
A quickstart script installs the binary on Linux, macOS or Windows, and a local instance is served on port 8000 with a web UI and an ingest HTTP API. The project also offers a hosted cloud version.
Key features
- 01Stores logs, metrics, traces and events as columnar Parquet on object storage.
- 02Includes alerting, dashboards, anomaly detection and APM in a single binary.
- 03Supports PromQL and SQL querying.
- 04Accepts data via OpenTelemetry, Kafka, eBPF and common logging agents.
- 05Separates stateless compute from object storage so each scales independently.
Use cases
- Centralizing application and infrastructure logs in a self-hosted observability stack.
- Replacing a multi-tool monitoring setup with one platform backed by S3.
- Monitoring AI agents and analyzing telemetry with LLMs.
- Using an existing OpenTelemetry Collector pipeline with a new backend.
Quick start
- 1
Run the official install script from the README
- 2
Send sample logs to the demo stream with the ingest command
curl --location --request POST 'http://localhost:8000/api/v1/ingest' \ --header 'X-P-Stream: demo' \ --header 'Authorization: Basic YWRtaW46YWRtaW4=' \ --header 'Content-Type: application/json' \ --data-raw '[ { "id": "434a5f5e-2f5f-11ed-a261-0242ac120002", "datetime": "24/Jun/2022:14:12:15 +0000", "host": "153.10.110.81" } ]' - 3
Open http://localhost:8000 and log in with admin / admin
Things to know
- Licensed under AGPL-3.0, a copyleft license that requires sharing source for modified versions.
- The quickstart uses default admin credentials, so production setups need the hardening steps in the installation guide.
In collections
Topics
FAQ
- What is parseable?
- Open source observability platform in Rust that stores logs, metrics, traces and events on object storage in a single binary. Parseable is an observability platform built on a data lake architecture. It ingests logs, metrics, traces and events from applications, agents and systems, and stores them in columnar Parquet format on object storage such as S3. Compute is stateless, so storage and processing can scale independently.
- Is parseable free to use? What license does it have?
- parseable is open source under the AGPL-3.0 license. Check the license terms before using it in commercial products.
- Is parseable still maintained?
- Actively maintained. The last commit to parseable was on Oct 23, 2026.
- What can I use parseable for?
- Centralizing application and infrastructure logs in a self-hosted observability stack. Replacing a multi-tool monitoring setup with one platform backed by S3. Monitoring AI agents and analyzing telemetry with LLMs. Using an existing OpenTelemetry Collector pipeline with a new backend.
- How do I install parseable?
- Run the official install script from the README Send sample logs to the demo stream with the ingest command: curl --location --request POST 'http://localhost:8000/api/v1/ingest' \ --header 'X-P-Stream: demo' \ --header 'Authorization: Basic YWRtaW46YWRtaW4=' \ --header 'Content-Type: application/json' \ --data-raw '[ { "id": "434a5f5e-2f5f-11ed-a261-0242ac120002", "datetime": "24/Jun/2022:14:12:15 +0000", "host": "153.10.110.81" } ]' Open http://localhost:8000 and log in with admin / admin
- Where can I get parseable?
- The source code and installation instructions are on GitHub: https://github.com/parseablehq/parseable
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