Columnar store for fast, lightweight logging
Founder here, Parseable is a lightweight log ingestion and query engine written in Rust. Parseable can ingest data from existing logging agents (FluentBit, LogStash, Vector, syslog-ng and more) using HTTP + JSON output. Ingested logs are stored as semi-indexed Parquet files (on disk or S3). You can query the data with builtin query engine using SQL or use a query engines of choice like Spark, Presto, Trino and so on. We also developed a Grafana data source plugin that lets you visualise log data via Grafana. Sample dashboard link in readme. As log data grew, our industry has responded with…
In plain words
Parseable is a lightweight log ingestion and query engine built in Rust that accepts data from common logging agents via HTTP and JSON. It stores logs as semi-indexed Parquet files on disk or S3, then queries them using SQL through a built-in engine or external tools like Spark and Trino. The system includes a Grafana plugin for log visualization. Designed for developers and operations teams who want full control over log data without relying on managed services.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Founder here, Parseable is a lightweight log ingestion and query engine written in Rust. Parseable can ingest data from existing logging agents (FluentBit, LogStash, Vector, syslog-ng and more) using HTTP + JSON output. Ingested logs are stored as semi-indexed Parquet files (on disk or S3). You can query the data with builtin query engine using SQL or use a query engines of choice like Spark, Presto, Trino and so on. We also developed a Grafana data source plugin that lets you visualise log data via Grafana. Sample dashboard link in readme. As log data grew, our industry has responded with SaaS and fully managed offerings, but if you're looking for freedom, interoperability and full control over your data - there are no great options. With Parseable, we are looking to provide an strong, viable and FOSS alternative.
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