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Together, Databricks and StreamSets give analytics leaders and developers more visibility into Apache Spark jobs and easier management of pipelines—no special skills required. Expand access to data with pre-built connections using native integration for Delta Lake and Apache Spark clusters running on Databricks, and visual tools to build and operate smart pipelines that detect and respond to change. It’s time to leverage the massive processing power of Apache Spark for ETL and machine learning.
Dynamically design change data capture (CDC) to manage syncing
Easily manage data drift with built-in detection and rule-based handling
Run natively on Spark on Databricks for high performance ETL and data processing
StreamSets visual tools make it easy to build and operate smart data pipelines that are Apache Spark native without specialized skills. Built-in efficient upsert functionality with Delta Lake simplifies and speeds Change Data Capture (CDC) and Slowly Changing Dimension (SCD) use cases. With custom processors your power users don’t have to hold back.
Stop hunting through log files and error strings, and focus on always-on alerts. StreamSets Data Integration Platform lets you monitor your Delta Lake ingestion pipelines and your Apache Spark applications in real-time plus you get built-in drift detection and handling. Bring the agility and scale of Apache Spark and deliver it with the confidence and visibility of powerful data integration.
StreamSets operationalizes the data value chain so you can go fast while ensuring continuous operations. The StreamSets Platform helps you quickly adopt high-performance engines like Databricks, so that you can accomplish more, and take advantage of modern data technologies to focus on business innovations.
Explore the pivotal role of data engineering in driving business value and innovation. Dive into our research on trends, challenges, and strategies for 2024.