Change Data Capture for a Brand New World - Hannu Valtonen

Discover how logical decoding and replication in Postgres revolutionize change data capture (CDC), enabling efficient tracking of database changes for data warehousing, auditing, and real-time analytics.

Key takeaways
  • Logical decoding and replication are revolutionary features introduced in Postgres 9.4 and 10, respectively, that allow for efficient and reliable change data capture (CDC).

  • CDC enables tracking all DML (insert, update, delete) operations on a database, providing a delta of changes that can be used for various purposes such as data warehousing, auditing, and real-time analytics.

  • The advent of logical decoding eliminates the need for complex and inefficient trigger-based approaches, which were commonly used in the past for CDC.

  • Logical replication allows for replicating data from one Postgres instance to another, including changes captured through logical decoding.

  • Streaming replication, a type of logical replication, enables real-time data replication, making it ideal for use cases such as continuous data integration and disaster recovery.

  • Apache Kafka is a popular streaming platform that can be used to publish and subscribe to change data captured from Postgres.

  • Debezium is an Apache Kafka connector that simplifies the process of capturing changes from Postgres and publishing them to Kafka topics.

  • Wall-to-json is a commonly used output plugin for logical decoding that converts the changes into JSON format, making them easy to consume by various applications and tools.

  • Change data capture can be used for a wide range of applications, including data warehousing, auditing, real-time analytics, and data migration.

  • It is important to consider the performance implications of CDC, as it can introduce additional overhead on the database server.

  • Proper setup and configuration of logical decoding and replication are crucial for ensuring reliable and efficient change data capture.