StreamSets, Inc., provider of a DataOps platform for modern data integration, is releasing StreamSets Transformer, a drag-and-drop UI tool to create native Apache Spark applications.
Designed for a wide range of users — even those without specialized skills — StreamSets Transformer enables the creation of pipelines for performing ETL, stream processing and machine-learning operations.
Now, data engineers, scientists, architects and operators gain deep visibility into the execution of Apache Spark while broadening usage across the business.
Key features of StreamSets Transformer include:
- Continuous monitoring — Unparalleled visibility into Apache Spark application execution
- Continuous data — Runs in both batch and streaming modes
- Progressive error handling — Finds where and why errors occur without the need for Apache Spark skills to decipher complex log files
- Execute on Apache Spark anywhere — Works in the cloud, Kubernetes or on premises
- Highly extensible — Higher order transformation primitives for the ETL developer, SparkSQL for the analyst, PySpark for the data scientist, and custom Java/Scala processors for the Apache Spark developer
- Sets-based processing — For ETL, machine learning and complex event processing
“With StreamSets Transformer, Apache Spark is finally available to a wide range of users, enabling visibility, monitoring, and reporting for mission-critical workloads,” said Arvind Prabhakar, CTO of StreamSets. “In essence, StreamSets Transformer brings the power of Apache Spark to businesses, while eliminating its complexity and guesswork.”
For more information about this news, visit www.streamsets.com.