Trifacta Partners With Databricks to Deliver Faster ROI on Data Lakehouses

Self-service solution removes data engineering bottlenecks, provides clean data and automated pipelines for analytics and machine learning

SAN FRANCISCO–(BUSINESS WIRE)–Trifacta, the Data Engineering Cloud company, today announced a partnership with Databricks, the Data and AI company, around a joint solution that natively integrates Trifacta’s interactive, visual data preparation capabilities into the Databricks Lakehouse Platform. This new joint solution accelerates the development and orchestration of data preparation pipelines by removing bottlenecks that slow data prep for analytics and machine learning models, all while tracking data lineage and ensuring sustainable data governance.

The joint solution has proved essential to organizations modernizing their analytics processes with cloud data lakes and warehouses. With the integration of Trifacta and Databricks platforms, a broader set of data workers can take ownership over the data preparation process and easily collaborate with data scientists and data engineers to better align data products and pipelines with business goals. This visual, low-code joint solution reduces the burden on engineering teams and accelerates an organization’s time-to-insight from data analytics.

“Trifacta offers 1-click data preparation for customers to explore and transform diverse data at scale,” said Michael Hoff, SVP of Business Development, Databricks. “This helps drive more data into Lakehouse for advanced cloud analytics and machine learning.”

“At ABN Amro, we’re focused on democratizing data to accelerate automated decision making. This requires an intuitive approach that allows business users and technical users to collaborate in building high-quality data products. The combination of Trifacta and Databricks enables this,” said Marcel Kramer, ABN Amro Head of Data Engineering.

Trifacta’s integration with Databricks includes support for Delta Lake, enabling data workers to accelerate the process of refining data to feed analytic workloads.

Any transformation executed in Trifacta is translated into runtime Spark code that executes via Databricks, while Databricks automatically scales processing execution based on the parameters of the transformation job. The result is faster, more reliable data pipelines that work as hard as analysts do.

“Data operations are more tightly synced than ever before; no longer are today’s organizations seeking to create siloed data marts or disjointed data teams. And the partnership between Trifacta and Databricks is a perfect example of that,” says Ash Vijayakanthan, Vice President of Alliances, Trifacta. “We’ve made it possible for business users to not only involve themselves in data preparation, but also in the creation and management of data pipelines, both of which were once considered highly technical work relegated to IT teams. We’re excited to see our joint customers yield far greater returns with the ability to accelerate the data preparation process on top of cutting-edge processing power.”

Trifacta offers support for all major cloud platforms; Databricks is available on Microsoft Azure and Amazon AWS. Get started with Trifacta for free today by signing up here.

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About Trifacta

The Trifacta Data Engineering Cloud leverages decades of innovative research in human-computer interaction, scalable data management, and machine learning to make the process of preparing data and engineering data products faster and more intuitive. Around the globe, tens of thousands of users at more than 10,000 companies, including leading brands like Deutsche Boerse, Google, Kaiser Permanente, New York Life and PepsiCo, are unlocking the potential of their data with Trifacta’s market-leading data engineering platform. Learn more at

About Databricks

Databricks’ mission is to accelerate innovation for its customers by unifying Data Science, Engineering and Business. Founded by the original creators of Apache Spark, Databricks provides a Unified Analytics Platform for data science teams to collaborate with data engineering and lines of business to build data products. Users achieve faster time-to-value with Databricks by creating analytic workflows that go from ETL and interactive exploration to production. The company also makes it easier for its users to focus on their data by providing a fully managed, scalable, and secure cloud infrastructure that reduces operational complexity and total cost of ownership. Databricks, venture-backed by Andreessen Horowitz, NEA and Battery Ventures, among others, has a global customer base that includes Viacom, Shell and HP. For more information, visit


Dana Stein

Matter Communications