Author(s): Rashmi
Originally published on Towards AI.
Kafka vs Kinesis (2026): A practical guide to streaming, use cases, architecture and code
Event streaming is the nervous system of modern data platforms: clickstreams, payments, logs, IoT telemetry, fraud signals, and ML features all come together as continuous events – and you have to reliably ingest, buffer, process, and promote them.
This article examines the concepts and architecture surrounding event streaming, focusing on two popular technologies, Apache Kafka and Amazon Kinesis. It discusses their differences, performance metrics, and practical use cases. Additionally, the guide provides flow diagrams and code examples to illustrate how to effectively implement these techniques, highlighting their importance in modern AI systems not only as data transport layers but also as memory systems that record and manage event sequences for better analytics and auditing.
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Published via Towards AI
