Delta Lake Integration in KQL Real-Time Analytics
Microsoft Fabric
Nov 21, 2023 11:00 PM

Delta Lake Integration in KQL Real-Time Analytics

by HubSite 365 about Microsoft

Software Development Redmond, Washington

Data AnalyticsMicrosoft FabricM365 Release

Enable KQL Database in Delta Lake for unified analytics across Microsoft Fabric with enhanced low-latency queries!

Microsoft has recently introduced support for Delta Lake in its Real-Time Analytics KQL Database as part of the "One logical copy" initiative. This new feature allows users to access KQL Database data in Delta Lake format, which is the chosen unified data lake table format for seamless integration across all Microsoft Fabric compute engines. With data stored in an optimized columnar format, the system supports complex analytical queries on various data types.

The implementation of OneLake availability merges the high-speed, low-latency querying capability of KQL Databases with Delta Lake's broad compatibility. Such integration allows the use of various other Fabric engines, including Power BI Direct Lake mode and others, offering users a versatile and unified data experience.

  • Unified data lake table format for seamless data processing
  • Optimized storage with full text indexing for complex queries
  • One-time logical copy management for cost-effective data handling
  • Support for both structured and semi-structured data types
  • Robust mechanism for batch processing into Parquet files
  • OneLake enables access at both database and table levels
  • Real-time analysis with low latency on KQL Database
  • Simplified access for larger datasets with high volume streaming

This integration offers customers the best of both worlds, letting them benefit from the high performance of querying within the KQL Database while also querying the same data in Delta Lake format using other Fabric engines like Power BI Direct Lake mode, Warehouse, Lakehouse, and others. By batching data into Parquet files, the KQL Database ensures the data is open and reusable while only incurring storage costs once upon enabling in OneLake.

To activate data availability in OneLake, users need to navigate to their KQL database or table details page and edit the OneLake folder setting. With this feature active, they will be able to access all new data in the chosen Delta parquet path within OneLake. Additionally, users have the option to create shortcuts from Lakehouse or Data warehouse, or directly query the data via Power BI Direct Lake mode for simplicity and ease of access.

Microsoft Fabric supports a comprehensive streaming architecture that enables customers to efficiently manage high volumes of streaming data with low latency. Eventstream captures data from various sources and channels it into the KQL Database, facilitating the creation of a medallion architecture pattern for data transformation.

This pattern is comprised of three layers—Bronze for raw data, Silver for deduplicated and enriched data, and Gold for aggregated data. Customers can expose any or all these layers in OneLake, optimizing the system for large data streams, while also enabling quick access to real-time analysis and reporting in Delta Lake.

Understanding the benefits of KQL Database and Delta Lake integration

With the integration of KQL Database with Delta Lake, users experience a streamlined approach to data management and analysis. This collaboration between services allows for a seamless and efficient way to analyze large volumes of data in real-time, leveraging the reliability and speed of both platforms. By simplifying data operations and reducing the complexity of managing multiple data formats, Microsoft ensures that businesses can focus more on insights and less on infrastructure challenges. The "One logical copy" concept not only economizes resources but also exemplifies Microsoft's commitment to innovation and continuous improvement in the realm of data analytics.

Read the full article Announcing Delta Lake support in Real-Time Analytics KQL Database

Databases - Delta Lake Integration in KQL Real-Time Analytics


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