Build ETL Pipelines without the Complexity
Turn big data into insights throughout your organization with the power of Apache Spark on Databricks, EMR, Azure HDInsight, and other Spark clusters. StreamSets Transformer is a modern ETL pipelines engine designed for developers and data engineers to build data transformations that execute on Apache Spark without Scala or Python skills.
Run Apache Spark anywhere now and in the future as your needs evolve.
Operationalize Your Data Transformations
Speed Apache Spark Adoption
Put Apache Spark at the fingertips of any data engineer. Use a simple, drag-and-drop UI to create highly instrumented pipelines for performing ETL, stream processing, and machine learning operations. StreamSets Transformer helps your team leverage Apache Spark to accelerate your data projects without deep Scala expertise. Advanced Spark developers can easily operationalize their code and automate critical Spark operations.
Run ETL Pipelines on Multiple Spark Platforms
Transformer is designed to run on all major Spark distributions for maximum flexibility. You can natively execute on Hadoop YARN, EMR, HDInsight, and Databricks platforms, and in containerized Spark environments such as Microsoft SQL Server 2019 Big Data Cluster. Run your development and production projects on multiple Spark platforms or support different business unit needs from a single tool without rework.
See What Changed and Respond Easily
Full visibility and unmatched resiliency in your pipelines means you can stop hunting through log files for errors when change happens. Transformer pipelines are instrumented to provide deep visibility into Spark execution so you can troubleshoot at the pipeline level and at each stage in the pipeline. Transformer offers the enterprise features and agility of legacy ETL tools, while revealing the full power and opportunity of Apache Spark.