Talend Accelerates the Journey to Lakehouse Paradigm with Expanded Databricks Partnership
REDWOOD CITY, Calif., April 8, 2020 – Talend announced its continued partner momentum with Databricks. With the Winter ’20 release of Talend Data Fabric, including Stitch Data Loader for data ingest, Talend now supports Delta Lake. The comprehensive support enables data ingestion into lakehouse environments where data warehouse management features are combined with low-cost storage. The additional support for Delta Lake combined with the enhanced integration and integrity capabilities in Talend Data Fabric enable the fast ingest and optimal processing of reliable, high-quality data for Databricks users to inform machine learning workloads and quickly unlock insights for their business.
Talend also announced the availability of Talend’s Stitch Data Loader in Databricks’ recently announced Data Ingestion Network of partners. This network, showcasing select Databricks partners, brings data teams closer to building the new data management paradigm, lakehouse, which combines the best elements of data lakes and data warehouses, enabling business intelligence and machine learning on all of a business’s data.
“Talend is an important addition to our new partner ecosystem, which was built to speed data ingestion access for our customers,” said Michael Hoff, SVP Business Development and Partners at Databricks. “Talend provides both a powerful integration platform for data engineers and a simple-to-use data ingestion tool for business analysts. This not only helps our customers get started fast, but also gives them a path forward for enterprise data management.”
In addition to extended support for Delta Lake in its recent Winter ’20 release, Talend Data Fabric supports Apache Spark 2.4 and Databricks Runtime 5.5 Long Term Support for optimal product performance. Talend also adds major advancements for Spark Dataset, which enables users to take advantage of performance enhancements for optimal Apache Spark processing.
“Working closely with Databricks, our joint customers can achieve higher performance and innovate faster by using Talend Data Fabric to move workloads to Databricks,” said Mike Pickett, SVP Business Development and Ecosystem at Talend. “We look forward to continued collaboration with one of the leading cloud data and AI platforms in the industry.”
These updates enable Talend to provide Databricks users with comprehensive data quality and governance features to support machine learning and advanced analytics, natively supporting the full power of Apache Spark and Delta Lake. Through this integration, users can access the scale and cloud benefits through a drag and drop interface, instead of manually coding data engineering jobs. Talend is integrated with both Azure Databricks and Databricks for AWS.
Talend Data Fabric is a hybrid integration and integrity platform that intelligently connects, integrates, and shares trusted data at any scale with seamlessly built-in quality and governance. The platform solves the data efficiency gap by turning a mass of siloed data to a flow of trustworthy data that anyone can use. Talend Data Fabric transforms data into a powerful, valuable, and strategic asset that can provide a real competitive advantage.
To learn more about how companies can quickly benefit from ingesting data workloads into Delta Lake using Talend’s Stitch Data Loader, please read this blog. For more information on the extended support for Databricks in Talend’s Winter ’20 release, please visit this blog and this page. To listen to a recorded webinar on the many new advancements in Talend Data Fabric, please view here.
Talend, a leader in cloud data integration and data integrity, enables companies to transform by delivering trusted data at the speed of business. Talend Data Fabric offers a single suite of apps that shortens the time to trusted data by solving some of the most complex aspects of the data value chain. Users can collect data across systems, govern it to ensure proper use, transform it to new formats and improve quality, and share it with internal and external stakeholders.