Change Data Capture
Change Data Capture (CDC) for Ingres
The Change Data Capture (CDC) for Ingres facilitates modern data integration and streaming by providing access to logical log records in a structured, easily consumable format. This feature enables you to develop sophisticated solutions for real-time data replication, advanced analytics, and event-driven architectures. Its core function is to expose the granular changes happening within an Ingres database, making these changes available for immediate processing by other systems.
CDC supports a wide array of mission-critical use cases across different verticals. By offering a continuous stream of data modifications, it empowers organizations to build more responsive, data-driven applications and maintain data consistency across distributed environments.
Key use cases include:
• Stream Processing Engines
• Replication
• Caching Layer
• Post Commit Trigger Framework
Stream Processing Engines: This capability is crucial for scenarios requiring immediate analysis of incoming data. Examples include real-time fraud detection in financial services, where anomalies need to be identified and acted upon instantly; sophisticated trading systems that depend on up-to-the-second market data; continuous manufacturing monitoring to detect defects or inefficiencies as they occur; and military or intelligence tracking for immediate situational awareness and rapid response. In these contexts, CDC provides the raw, real-time data necessary for stream processing engines to perform complex event processing and make informed decisions.
Replication: CDC is fundamental for robust data replication strategies. This includes enabling high availability configurations, ensuring continuous operation even in the event of system failures; facilitating disaster recovery plans by maintaining up-to-date copies of data in separate locations; supporting workload partitioning by distributing read and write operations across multiple database instances; aiding in data consolidation efforts by bringing data from various sources into a central repository; and streamlining cloud migration projects by replicating on-premises data to cloud-based databases with minimal downtime. CDC ensures that replicas are always synchronized with the primary database, providing a consistent view of the data.
Caching Layer: Efficient cache invalidation is vital for maintaining data consistency in high-performance applications that utilize caching layers like Memcached or Redis. When data in the underlying Ingres database changes, the CDC can trigger immediate invalidation of the corresponding outdated cache entries. This prevents applications from serving stale data, improving data accuracy and user experience, especially in scenarios with frequently updated information.
Post-Commit Trigger Framework: This feature allows for the execution of user-defined code or business logic in response to specific data changes. By leveraging the change streams exposed by CDC, organizations can implement powerful event-driven actions. Examples include alerting on large deposits or suspicious transactions in banking applications, providing real-time leaderboards in gaming applications, triggering automated workflows based on inventory level changes, or updating external systems whenever a new customer record is created. This framework transforms the database into an active participant in business processes, enabling immediate reactions to critical events.
Last modified date: 01/27/2026