Overview

Practical Striim: Building and Operating Real-Time Data Pipelines for Change Data Capture and Analytics is a hands-on guide for engineers, architects, and technical leaders who need to design, build, and operate production-grade streaming data solutions with Striim. Beginning with a clear, practical overview of real-time architectures and deployment topologies, the book explains why Striim's unified approach to streaming, CDC, and real-time analytics is uniquely suited to both cloud-native and hybrid environments. It frames core concepts-events, windows, time semantics, and CDC patterns-through pragmatic use cases, helping readers translate theory into reliable, maintainable pipeline designs. The middle section dives into implementation: step-by-step walkthroughs of real-time ETL pipelines, stateful aggregation, complex event processing, out-of-order event reconciliation, and schema evolution. Readers learn to integrate a broad set of sources and targets-from relational databases and NoSQL stores to cloud data warehouses and analytics platforms-while leveraging Striim Query Language (TQL), CI/CD best practices, and built-in observability to deploy, test, and debug pipelines at scale. Modular examples and patterns show how to manage data lineage, ensure idempotency, handle backpressure, and automate deployments for repeatable, auditable delivery. Rounding out the book are operational and enterprise concerns: scaling strategies, resource optimization, high availability, disaster recovery, compliance, and privacy enforcement are all covered with actionable guidance for production operations. Advanced chapters explore AI/ML pipeline integration, edge and IoT streaming, and strategies for modernizing legacy systems with CDC-driven migrations. Concluding with a forward-looking survey of emerging trends and relevant open-source tools, Practical Striim prepares teams to build resilient, observable, and performant real-time data platforms that drive analytics and business value.

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