PgBouncer vs TiCDC

PgBouncer is a self-hosted connection pooler for PostgreSQL. It reuses server connections to lessen the performance cost of opening new ones, and offers session, transaction, and statement pooling. Statement pooling does not allow multi-statement transactions. PgBouncer can send connections to databases on different hosts, but it has no built-in multi-host load balancing or failover detection; DNS round-robin, external TCP load balancers, DNS changes, or external tools are described as alternatives. It can track protocol-level prepared statements in transaction and statement modes when max_prepared_statements is non-zero. Authentication options include client certificates, SCRAM-SHA-256, LDAP, PAM, and HBA-based configuration. The features page lists default memory needs of 2 kB per connection. PgBouncer is free, with source releases and references to native packages and RPM and Debian repositories. It runs on Linux and Windows; MinGW is the documented supported Windows build environment. Building requires Libevent 2.0 or later, pkg-config, and a C11-capable compiler; TLS support also requires OpenSSL.

TiCDC is a free, open-source, self-hosted tool for replicating incremental data changes from TiDB. It captures TiKV change logs, sorts the changes, and exports row-based data to systems including TiDB, MySQL-compatible databases, Kafka, Amazon S3, GCS, Azure Blob Storage, and NFS. Recommended Kafka formats include Canal-JSON, Avro, and Debezium. Filters can select databases, tables, DMLs, and DDLs, while the Open API can check task status, change task configuration, and create or delete tasks. TiCDC supports replication between TiDB clusters for disaster recovery, with second-level RPO and minute-level RTO, as well as bidirectional replication for multi-active deployments. It can be deployed with a new cluster or added to an existing one; production guidance recommends at least two instances. The system has no single point of failure and allows nodes to be added or removed dynamically. Delivery is at least once, so failures can lead to repeated statements or Kafka messages.