Parallel Pipelines
Parallel pipelines are a software design pattern and architectural concept that involves executing multiple data processing or workflow stages concurrently to improve performance and throughput. They enable tasks to be divided into independent stages that can run in parallel, often using multiple processors, threads, or distributed systems. This approach is commonly used in data engineering, CI/CD, and high-performance computing to optimize resource utilization and reduce latency.
Developers should learn and use parallel pipelines when dealing with large-scale data processing, real-time analytics, or complex workflows where sequential execution becomes a bottleneck. Specific use cases include ETL (Extract, Transform, Load) processes in big data applications, continuous integration and deployment pipelines that run tests and builds concurrently, and streaming data systems that require low-latency processing. It is essential for improving scalability and efficiency in modern distributed systems.