Event-driven architecture best practices for databases and files

The current data integration landscape, dominated by poll-based ETL pipelines, creates challenges due to the added load on source data systems and the resulting outdated data in downstream systems. These traditional pipelines often require full table scans, leading to performance issues and high costs, while also failing to support real-time data applications due to inherent latency. As a solution, the text explores event-driven architectures, which trigger data ingestion based on events, allowing data to be processed immediately and reducing the strain on source systems. Event-driven architectures use approaches like event streaming, message queuing, and serverless functions to provide fresher data and support real-time use cases. Change Data Capture (CDC) is also discussed as a viable alternative when backend code modifications are not feasible, leveraging database logs to capture changes without additional load on the application database. The text highlights the benefits of using modern cloud storage services for event-driven file ingestion, which enhance data freshness and system robustness. Although message queues are preferred for their flexibility and durability, serverless functions can trigger processes directly for simpler use cases, though they may lack the flexibility of message queues. Ultimately, transitioning to event-driven architectures can enable real-time data processing, crucial for applications requiring immediate data access.