| From: | burnside project via PostgreSQL Announce <announce-noreply(at)postgresql(dot)org> |
|---|---|
| To: | PostgreSQL Announce <pgsql-announce(at)lists(dot)postgresql(dot)org> |
| Subject: | pg-cdc Frustratingly simple Postgres change data capture to AWS S3 |
| Date: | 2026-07-05 16:22:12 |
| Message-ID: | 178326853237.108999.11396238148836816033@wrigleys.postgresql.org |
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| Lists: | pgsql-announce |
Core Features
git Repo: [https://github.com/burnside-project/pg-cdc](https://github.com/burnside-project/pg-cdc)
pg-cdc is not just replication. pg-cdc streams Postgres Write Ahead Logs(WAL) out of production Postgres into typed, immutable, time-travelable Iceberg tables on S3
Registers each entities in the AWS Glue Catalog
Gates every read with AWS Lake Formation tags — so AI agents, analysts, and query engines consume governed data without ever touching the source database, and without database credentials.
No JVM. One binary.
No return path — the WAL is one-way; Parquet is immutable. Agents physically cannot write to production.
No database credentials — consumers authenticate via AWS IAM + Lake Formation, never a connection string.
Governed by default — untagged data is invisible; Lake Formation tags gate every read, down to the column.
Time travel built in — every flush is an Iceberg snapshot; CDC epochs + immutable raw@<ts> tags give historical queries with no database branching.
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