All the ways to do change data capture in Postgres

Change Data Capture (CDC) in Postgres helps address the need for real-time data streaming and workflow triggers by capturing and delivering changes made to data in a database to downstream systems. Various methods for implementing CDC in Postgres include Listen/Notify, which uses Postgres' interprocess communication feature but has limitations such as transient notifications and payload size restrictions; polling the table, which is robust but cannot detect deletions or provide data diffs; and audit tables, which log changes but can lead to write amplification and scaling issues. Foreign Data Wrappers (FDWs) offer a way to read and write to external data sources but are complex and less suitable for change capture. Logical replication offers a robust solution by using Postgres' write-ahead-log (WAL) but is complex and requires specific management strategies. Sequin, a third-party tool, utilizes logical replication to stream Postgres changes to various queues, streams, and endpoints, simplifying the process by abstracting complexities and ensuring exactly-once processing guarantees. Each method has its own advantages and downsides, making the choice dependent on specific use cases and requirements.

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