https://community.databricks.com/t5/announcements/modernize-your-data-engineering-platform-with-lakeflow-on-azure/m-p/149156#M623 <P><SPAN>Databricks Lakeflow on Azure provides a modern, enterprise-ready, and reliable data engineering platform for unified ingestion, transformation, and orchestration. It gives data engineers a single, Azure-native platform to ingest, transform, and orchestrate data with built-in governance, observability, and serverless performance. Teams can replace disjointed tools and manual glue code with a unified, governed experience that accelerates pipeline delivery and improves reliability.</SPAN></P> <P><STRONG>Key highlights:&nbsp;</STRONG></P> <P><STRONG>Unified data engineering:</STRONG><SPAN>&nbsp;</SPAN></P> <UL> <LI><SPAN>End-to-end platform for ingestion, transformation, and orchestration in one place with Lakeflow Connect, Spark Declarative Pipelines, and Lakeflow Jobs.</SPAN></LI> <LI><SPAN>Support for both batch and streaming workloads, plus declarative ETL patterns (including incrementalization and SCD Type 1 &amp; 2) with just a few lines of code.</SPAN></LI> </UL> <P><SPAN>​</SPAN><STRONG>Built-in governance and observability</STRONG></P> <UL> <LI aria-level="2"><SPAN>Native Unity Catalog integration for centralized identity, fine-grained permissions, and end-to-end lineage from ingestion through Lakeflow Jobs to downstream analytics and Power BI.</SPAN></LI> </UL> <UL> <LI aria-level="2"><SPAN>System Tables and Lakeflow Jobs observability to monitor pipeline health, failures, performance bottlenecks, and error trends in a single UI.</SPAN></LI> </UL> <P><STRONG>Performance, cost, and reliability at scale</STRONG></P> <P>&nbsp;</P> <UL> <LI><SPAN>Serverless data processing and cluster reuse to reduce idle waste, cut operational overhead, and optimize spend across workloads.</SPAN></LI> <LI><SPAN>Customers on Azure have reported up to 25x faster pipeline development, performance gains up to 90x, and ETL cost reductions of up to 83% with Lakeflow.</SPAN></LI> </UL> <P><STRONG>Flexible experience for every user</STRONG></P> <UL> <LI><SPAN>Code-first authoring with Lakeflow Pipeline Editor, Databricks Asset Bundles, and SDKs for developers who want full control.</SPAN></LI> <LI aria-level="2"><SPAN>Intuitive point-and-click experiences and APIs for newcomers and business users to configure ingestion and orchestrate workloads without deep infra knowledge.</SPAN></LI> </UL> <P><LI-WRAPPER><SPAN>Check this </SPAN><A href="https://www.databricks.com/blog/modernize-your-data-engineering-platform-lakeflow-azure-databricks?utm_source=bambu&amp;utm_medium=social&amp;utm_campaign=advocacy" target="_blank"><SPAN>article</SPAN></A><SPAN> for complete details on how to use Lakeflow on Azure Databricks, and start modernizing your data engineering platform today.</SPAN></LI-WRAPPER></P> Tue, 24 Feb 2026 11:21:26 GMT Om_Jha 2026-02-24T11:21:26Z https://community.databricks.com/t5/announcements/modernize-your-data-engineering-platform-with-lakeflow-on-azure/m-p/149156#M623 <P><SPAN>Databricks Lakeflow on Azure provides a modern, enterprise-ready, and reliable data engineering platform for unified ingestion, transformation, and orchestration. It gives data engineers a single, Azure-native platform to ingest, transform, and orchestrate data with built-in governance, observability, and serverless performance. Teams can replace disjointed tools and manual glue code with a unified, governed experience that accelerates pipeline delivery and improves reliability.</SPAN></P> <P><STRONG>Key highlights:&nbsp;</STRONG></P> <P><STRONG>Unified data engineering:</STRONG><SPAN>&nbsp;</SPAN></P> <UL> <LI><SPAN>End-to-end platform for ingestion, transformation, and orchestration in one place with Lakeflow Connect, Spark Declarative Pipelines, and Lakeflow Jobs.</SPAN></LI> <LI><SPAN>Support for both batch and streaming workloads, plus declarative ETL patterns (including incrementalization and SCD Type 1 &amp; 2) with just a few lines of code.</SPAN></LI> </UL> <P><SPAN>​</SPAN><STRONG>Built-in governance and observability</STRONG></P> <UL> <LI aria-level="2"><SPAN>Native Unity Catalog integration for centralized identity, fine-grained permissions, and end-to-end lineage from ingestion through Lakeflow Jobs to downstream analytics and Power BI.</SPAN></LI> </UL> <UL> <LI aria-level="2"><SPAN>System Tables and Lakeflow Jobs observability to monitor pipeline health, failures, performance bottlenecks, and error trends in a single UI.</SPAN></LI> </UL> <P><STRONG>Performance, cost, and reliability at scale</STRONG></P> <P>&nbsp;</P> <UL> <LI><SPAN>Serverless data processing and cluster reuse to reduce idle waste, cut operational overhead, and optimize spend across workloads.</SPAN></LI> <LI><SPAN>Customers on Azure have reported up to 25x faster pipeline development, performance gains up to 90x, and ETL cost reductions of up to 83% with Lakeflow.</SPAN></LI> </UL> <P><STRONG>Flexible experience for every user</STRONG></P> <UL> <LI><SPAN>Code-first authoring with Lakeflow Pipeline Editor, Databricks Asset Bundles, and SDKs for developers who want full control.</SPAN></LI> <LI aria-level="2"><SPAN>Intuitive point-and-click experiences and APIs for newcomers and business users to configure ingestion and orchestrate workloads without deep infra knowledge.</SPAN></LI> </UL> <P><LI-WRAPPER><SPAN>Check this </SPAN><A href="https://www.databricks.com/blog/modernize-your-data-engineering-platform-lakeflow-azure-databricks?utm_source=bambu&amp;utm_medium=social&amp;utm_campaign=advocacy" target="_blank"><SPAN>article</SPAN></A><SPAN> for complete details on how to use Lakeflow on Azure Databricks, and start modernizing your data engineering platform today.</SPAN></LI-WRAPPER></P> Tue, 24 Feb 2026 11:21:26 GMT https://community.databricks.com/t5/announcements/modernize-your-data-engineering-platform-with-lakeflow-on-azure/m-p/149156#M623 Om_Jha 2026-02-24T11:21:26Z