Apache Storm

About Apache Storm

Real-time computation system making it easy to process unbounded streams of data reliably. Fast and scalable distributed real-time computation framework for stream processing.

Key Features

• 1Real-time stream processing with guaranteed message processing semantics
• 2Topology-based architecture defining spouts (sources) and bolts (processors)
• 3Horizontal scalability by adding workers to running topologies
• 4At-least-once and exactly-once processing guarantees via transactional topologies
• 5Integration with Kafka, HDFS, HBase, and other ecosystem components

How Python Data Engineers Use Apache Storm

Python data engineers use Apache Storm via the streamparse library to write Storm topologies in Python. Storm is used for real-time event processing, fraud detection, and IoT telemetry pipelines where data must be processed and acted upon within milliseconds. While Kafka Streams and Flink have largely superseded Storm in new builds, it remains in production at organisations processing high-velocity event streams.