Setting up replication from a PostgreSQL database (A) to another PostgreSQL database (B) as a standby, and additionally replicating specific tables from PostgreSQL (A) to a ClickHouse database (C) as a standby, involves several steps and components. This setup ensures data consistency across different database systems and enables leveraging ClickHouse for analytics or reporting purposes on data originating in PostgreSQL. Here's how to approach this scenario:

Step 1: Replicating PostgreSQL A to PostgreSQL B (Standby)

1. Configure PostgreSQL Replication:
   • On PostgreSQL A (Primary): Configure PostgreSQL for replication by editing the postgresql.conf file to set the wal_level to replica, archive_mode to on, max_wal_senders to a value greater than 0, and specify the archive_command to safely store WAL files. Also, adjust the pg_hba.conf file to allow connections from the standby server (B).
   • On PostgreSQL B (Standby): Set up the standby server by creating a recovery.conf file in the PostgreSQL data directory, specifying the connection details to the primary server (A), and using the standby_mode setting. You may use tools like pg_basebackup to initialize the standby server with a copy of the primary database.

Step 2: Setting up Replication from PostgreSQL A to ClickHouse C

To replicate specific tables from PostgreSQL (A) to ClickHouse (C), you can use different approaches such as custom scripts, third-party tools like pg_chameleon or Debezium with Kafka, or direct database links if supported by future versions or plugins.

Option 1: Using Debezium and Kafka for Real-Time Replication:

1. Setup Kafka: Kafka acts as a middleman for capturing changes from PostgreSQL and streaming them to ClickHouse.
2. Configure Debezium: Debezium captures row-level changes from PostgreSQL and publishes them to Kafka topics. Install and configure Debezium Connector for PostgreSQL to capture changes from your primary PostgreSQL database (A).
3. Stream to ClickHouse: Use a tool like kafka-engine in ClickHouse or a custom consumer script that reads messages from Kafka topics and inserts them into ClickHouse tables.

Option 2: Using Direct Inserts or Custom Scripts:

1. Custom Scripts: Write custom scripts that extract data from PostgreSQL and insert it into ClickHouse. This can be based on triggers or scheduled jobs.
2. Cron Job: A scheduled cron job could periodically export data from PostgreSQL and import it into ClickHouse using clickhouse-client or other data import methods.

Important Considerations:

• Schema Compatibility: Ensure the table schema in ClickHouse is compatible with the data types in PostgreSQL. You might need to create corresponding tables in ClickHouse manually or script them to match the source tables in PostgreSQL.
• Data Transformation: Depending on your use case, data might need to be transformed before being inserted into ClickHouse. This could be due to differences in data types or the need for aggregation.
• Monitoring and Error Handling: Implement robust monitoring and error handling for the replication processes to quickly identify and rectify issues.

Conclusion

Setting up this replication architecture requires careful planning, especially in terms of network configuration, security (e.g., ensuring encrypted connections), and data consistency checks. Always test your replication setup in a staging environment before moving to production to ensure everything works as expected and to minimize downtime or data loss.