Stream join
Join independent stream events to trigger advanced analytics and dynamic business rules
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Join independent stream events to trigger advanced analytics and dynamic business rules
Last updated
Was this helpful?
The join operation in stream processing is a powerful function that accelerates time-to-insight by correlating multiple event streams into a cohesive, meaningful flow. This is essential for scenarios requiring real-time data analysis.
Unlike real-time data enrichment, which supplements data with computed or static data sets, stream joining focuses on combining live events for immediate insights and improve customer engagement.
Ad Performance tracking in real-time Track ad clicks, impressions, and user actions in real-time to refine ad spend and gather customer insights.
Dynamic promotions Detect new leads on your site, track product interactions, and apply promotional rules to deliver tailored promotions.
Product recommendations Combine user sessions, viewed ads, and clicks to generate personalised product suggestions, with feedback loops for ongoing improvement.
Customer 360 proactive support Analyse multiple customer telemetry streams to provide proactive, personalised support and enhance the customer experience.
Platform anomaly detection Monitor and analyse telemetry from devices to detect unusual compute or network usage patterns, supporting operational efficiency and reliability.
On the Joule platform, there are two types of joins available.
Inner stream joins
Strict join between two event streams
Outer stream joins
Immediately pass the first event received and initialised downstream processors
Join attributes & policy
Join attributes to control and optimise performance
