pgagroal vs TiCDC

pgagroal is a free, self-hosted PostgreSQL connection pool for Linux and macOS. It supports per-user and per-database connection limits, pool prefill, idle connection removal, and connection validation. Administrators can enable or disable database access and choose graceful or fast shutdown. Remote management and command-line tools handle runtime administration and user management. Monitoring exports Prometheus metrics and includes a Grafana 12 dashboard. Authentication can use database-backed queries or a user vault for credentials. If a PostgreSQL server can no longer accept writes, pgagroal can trigger an external failover workflow. The project lists TLS v1.2+ and describes both server-only and mutual certificate authentication. It works with PostgreSQL-compliant drivers including pgjdbc, Npgsql, and pq. Tested systems listed include Fedora 38+, RHEL 9.x, Rocky Linux 9.x, FreeBSD, and OpenBSD; releases list packages through Fedora 42/43, RHEL 10, and Rocky Linux 10. The repository identifies a BSD-3-Clause license. GitHub is used for questions, issues, feature requests, and code contributions.

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.