# getdozer/dozer

Dozer is a real-time data movement tool that leverages CDC from various sources and moves data into various sinks.

Repository: https://github.com/getdozer/dozer
Canonical: https://ross.abutalabs.com/products/getdozer-dozer
Homepage: https://getdozer.io
Language: Rust
License: AGPL-3.0
License Family: copyleft
Topics: apis, data, rust, sql, realtime, streaming, etl, low-code, postgres, snowflake, api, clickhouse, datawarehouse, debe
Last push: 2024-06-18T22:23:39+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1463, "days_push": 806, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1579, forks 140 (observed 2026-08-28T04:05:06.762675+00:00)

## What it is
Dozer is a real-time data movement tool written in Rust that captures change data (CDC) from sources like Postgres, MySQL, Snowflake, and Kafka and streams it into sinks such as ClickHouse, BigQuery, and data warehouses. It is configured via a single YAML file and claims to be significantly faster than a Debezium+Kafka pipeline.

## Use cases
- stream postgres changes to clickhouse in real time
- cdc data pipeline without kafka
- sync mysql database to a data warehouse
- move data from s3 into bigquery continuously
- build real-time data apis on top of a warehouse
- replace debezium with a faster data replication tool
- low-code etl configured with a single yaml file

## When to choose
- you need low-latency, real-time replication from operational databases into warehouses or analytics stores
- you want a simpler, faster alternative to a Debezium + Kafka stack
- your sources and sinks are among the supported ones (Postgres, MySQL, Snowflake, Kafka, MongoDB, S3, GCS into ClickHouse, Postgres, MySQL, BigQuery)

## When to avoid
- you need batch-only ETL with complex transformations rather than CDC streaming
- you require Oracle or Aerospike connectors, which are enterprise-only
- you need connectors with fully supported resuming for MongoDB, S3, or GCS, which are still incomplete
- your sources or sinks are not on the supported list

## Facets
- artifact type: application
- maturity: active
- function: etl, streaming, database, data-science
- domain: databases, analytics, big-data
- platform: self-hosted, rust, cli
- tags: cdc, change-data-capture, data-pipeline, real-time, data-warehouse, clickhouse, postgres, snowflake, debezium-alternative, low-code, data-engineering, linux, macos, docker

## Member repositories
- getdozer/dozer (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:06.762675+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:56:43.549975+00:00, confidence not recorded.
  - readme: https://github.com/getdozer/dozer (fetched 2026-08-28T04:05:06.762675+00:00, sha e5f1a18743e0)
- Data as of 2026-08-30T08:39:29.467469+00:00.