Streaming (data)
Processing data continuously as it arrives rather than in batches. Event streams from Kafka or AWS Kinesis allow automations to process millions of small events per second essential for real-time inventory, pricing, and fraud detection.
Expert insight
Streaming data processing (acting on data continuously as it arrives, rather than in periodic batches) suits genuinely real-time use cases but adds meaningful complexity around out-of-order events and exactly-once processing guarantees, worth confirming the use case actually needs streaming before taking on that complexity over simpler batch processing.
In a real workflow
Website events are streamed to analytics as they happen.
Common mistakes
- Streaming data that is only needed daily.
- No handling of late events.
Complexity level
Technical term used in production automation systems.
See it in action
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Go deeper
Guides that cover Streaming
Logic Apps vs Power Automate for Moving SharePoint Files (and a Third Option)
A direct comparison of Logic Apps and Power Automate for SharePoint file moves, where both platforms struggle, and where n8n wins on large files and cross-platform workflows.
n8n HTTP Request Node: Complete Documentation and Examples
The HTTP Request node is the most used node in n8n, connecting your workflows to any API or web service. This guide covers every configuration option, authentication method, error handling pattern, and real-world example you need.
5 Zapier Free Alternatives That Handle Real Production Workloads
Zapier is expensive at scale. These 5 alternatives n8n, Make, Pipedream, Activepieces, and Albato handle real production workloads. Here is what each actually costs and where each breaks.