A practical guide comparing batch and streaming data pipelines in Python. Covers the architectural differences, tradeoffs, and when to use each approach. Includes working Python code for both patterns using pandas for batch ETL and generator functions for streaming event processing. Also explains hybrid architectures like Lambda and Kappa for systems that need both. Key decision factors: data freshness requirements, processing complexity, and operational capacity. The recommendation is to default to batch and only adopt streaming when a concrete real-time requirement demands it.
Table of contents
PrerequisitesTable of ContentsWhat Is a Batch Pipeline?What Is a Streaming Pipeline?The Key Differences at a GlanceChoosing Between Batch and StreamingThe Hybrid Pattern: Lambda and Kappa ArchitecturesConclusionSort: