A self-hosted event tracking and raw-storage pipeline for product, application, and game analytics. Open source under Apache 2.0, designed for teams that want to keep control of their event data and avoid vendor lock-in.
RawbbitEvent is the ingestion and raw-storage layer of a portable analytics system. In its current public shape, producers send event batches over HTTP, the collector validates and enriches them, NATS JetStream buffers the write path, and a raw writer lands partitioned Parquet files in object storage.
The supported query path builds on that raw layer: Parquet files can be exposed through a BigQuery external table, and the repository also includes a small SQLMesh starter project for downstream modeling. The raw Parquet layer stays the system-of-record boundary.
Producer → Collector API → NATS JetStream → Raw Writer → Parquet in object storage
HTTP ingestion service. Accepts and validates event batches at POST /v1/events:batch, then enriches the accepted events before publishing them into the stream.
Message broker between the collector and the writer. It separates request handling from storage writes and provides buffering and durability between ingestion and raw-file landing.
JetStream consumer that writes partitioned Parquet files to object storage. The raw Parquet layer is the durable system-of-record boundary for downstream analytics work.
Your choice of Google Cloud Storage or an S3-compatible backend such as SeaweedFS. The documented BigQuery external-table path currently uses GCS.
Query raw Parquet directly through BigQuery without loading the data into managed tables first. The raw layer stays portable while the warehouse becomes a query surface.
Included downstream modeling layer. It reads from the BigQuery external table over raw Parquet and provides a small starting point for downstream shaping, not a full modeling system.
The current release is intentionally narrow: it focuses on reliable ingestion, durable raw storage, and a simple first query path.
Rawbbit is released under the Apache 2.0 License.
All source code, documentation, deploy scaffolding, and the starter SQLMesh project are public on GitHub.
Self-host it freeUse the open-source repository for the self-serve path, or book a setup call if you want the fastest route to a working deployment.