May 2026
Intermediate to advanced
370 pages
10h 34m
English
Content preview from Real-Time Intelligence with Microsoft Fabric
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Chapter 6. Fabric’s Eventhouse Service
As we discussed in Chapter 1, Fabric offers three data storage paradigms to meet diverse organizational needs: data warehouses, lakehouses, and the newly introduced eventhouses. While data warehouses and lakehouses are established concepts for batch processing, the eventhouse was specifically engineered for the demands of Real-Time Intelligence.
Eventhouses are made to ingest, store, and process large amounts of data at very low latency. And while the name suggests it is separate from KQL databases, Eventhouse serves as the management layer of the clusters and databases that comprise the KQL technology. Microsoft has even started referring to eventhouses for KQL databases as “workspaces,” and each eventhouse hosts one or more KQL databases.
In this chapter, you will explore both eventhouses and KQL databases because they are closely connected. By understanding the synergy between the Eventhouse management layer and the KQL database engine, you can build a high-performing foundation for any real-time analytical scenario. (You’ll learn more about KQL as a language in Chapter 9.)
Evolution and Purpose of Eventhouses and KQL Databases
While Fabric is a modern unified platform, the technology powering Eventhouse and KQL databases is remarkably mature. In this section, we’ll review the history of this technology to help you understand why it’s well suited to today’s high-velocity data demands.
KQL technology emerged from Microsoft’s internal ...
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