dbmazz vs pgstream

dbmazz is a Rust daemon for moving database changes into a sink. It reads PostgreSQL changes through logical replication and streams inserts, updates, and deletes. The project lists PostgreSQL and MySQL as sources, and StarRocks, PostgreSQL, and Snowflake as stable sinks; S3/Iceberg is planned. Each instance handles one replication job. The project reports sub-second replication lag and about 11 MB of resident memory per daemon. Teams can try its ez-cdc CLI quickstart or run the daemon from the official Docker image. The CLI supports Linux and macOS on amd64 and arm64. Listed observability tools include Prometheus metrics, gRPC reflection, an HTTP control plane, and a live terminal dashboard. Automatic setup can create publications, replication slots, sink tables, and audit columns. Self-hosting is free; BYOC is also listed at free in a customer's AWS or GCP account, while support and optional PrivateLink cost extra. The Elastic License 2.0 permits commercial and non-commercial use but restricts offering the software to third parties as a managed service.

pgstream is a free, open-source tool for moving PostgreSQL data and schema changes to other systems. Run it as a command-line program or embed it as a Go library; it is self-hosted and requires PostgreSQL. Destinations include PostgreSQL, Elasticsearch or OpenSearch, Kafka, and webhooks. It can take an initial or on-demand snapshot for bulk loads and point-in-time copies, and tracks schema changes so receiving systems can reflect table updates. During replication, column values can be transformed with greenmask, neosync, go-masker, or custom transformers, including to mask production data headed for development or staging. Kafka support includes schema-based partitioning. Installation options include a Go binary, building from source, and Homebrew on macOS or Linux. The project uses the Apache License 2.0 and costs nothing. Its initial release has constraints: one Kafka topic, the wal2json PostgreSQL plugin, no row-level filtering, and a primary-key or unique non-null column requirement. Community questions and issues go through GitHub issues.