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Fluss is a compelling new project in the realm of real-time dataprocessing. Kafka is designed for streaming events, but Fluss is designed for streaming analytics. Architecture Difference The first difference is the Data Model. The fourth difference is the Lakehouse Architecture.
Streams of data are continuously queried with Streaming SQL , enabling correlation, anomaly detection, complex event processing, artificial intelligence/machine learning, and live visualization. Because of this, streaming analytics is especially impactful for fraud detection, log analysis, and sensor dataprocessing use cases.
One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure DataLake Store. It does away with the requirement to import data from an outside source. Export information to Azure DataLake Store, Azure Blob Storage, or Hadoop.
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