Cloudera Data Engineering 1.23: Access Spark from Your Favorite IDE and Optimize Workflows with Airflow 2.9 and Iceberg 1.5

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We are thrilled to share the latest release of Cloudera Data Engineering 1.23 on public cloud. With major enhancements for developer experience and product stability, this release enables you to benefit from increased productivity and collaboration while ensuring enterprise-grade security. 

Discover New Benefits & Features

• Boosted Development Productivity: The External IDE Connectivity (Tech Preview) powered by Apache Spark Connect enables practitioners to run large-scale Spark workloads remotely on Cloudera Data Engineering. That means you can access Spark from your favorite IDE and collaborate more efficiently with your team.

 

• Optimized, Cost-Effective Workflows: Support for Apache Airflow 2.9 and Python 3.11 expands access to the latest libraries and frameworks, equipping you with tools to meet your dynamic needs for building scalable data pipelines. Apache Iceberg 1.5, together with the support of Apache Spark 3.5, delivers better overall performance and cost management. For example, in use cases such as Change Data Capture (CDC), improvements in row-level deletes with Merge-on-Read enable more efficient query processing. This results in faster query execution and reduced resource consumption, leading to potential cost savings.
• Improved Administrative Capabilities: We strengthened stability with In-Place Upgrade and Backup & Restore to ensure a reliable and smooth upgrade experience. 

Ready to Learn More?

• View Product Release Notes, Compatibility and Runtime Components for Cloudera Data Engineering
• Start your 5-day trial for Cloudera Data Engineering on AWS 
• Download the new datasheet for Cloudera Data Engineering