Summary
This chapter provided an extensive overview of various data integration techniques, aiming to equip you with an understanding of diverse models, architectures, and patterns employed in data integration. This chapter began by comparing point-to-point integration and middleware-based integration, elaborating on their respective advantages, disadvantages, and use cases. Then, we transitioned to a comprehensive review of data integration architectures while discussing the mechanics, trade-offs, and applicability of batch, micro-batching, real-time, and incremental data integration. Next, we explored popular data integration patterns, including ETL and ELT, along with several others, such as CDC and data federation. Finally, we covered data integration organizational models, providing a deep dive into the traditional (monolithic) architecture, the data mesh model, and the data lake architecture. We concluded by offering guidance on choosing the right integration model, with a detailed...
