Hevo Data Partners with Databricks to Bring Effortless and Automated Data Integration to More Data-Driven Businesses

Hevo Data, the leading no-code ETL platform, announced their official partnership with Databricks, the lakehouse company, to simplify and accelerate data integration into the lakehouse for mutual customers. This new partnership allows users to access Hevo Data directly in Databricks and redefines data integration at scale.

As data continues to enable operational and strategic business decisions, data lakehouses like Databricks, which combine the best of data warehouses and data lakes, offer businesses a single platform to combine all their data, analytics, and AI operations.

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Yet, data teams struggle to reliably bring together the data that’s siloed in dozens of business softwares, often requiring months of effort in setting up and maintaining ETL pipelines. Hevo Data’s intuitive, no-code platform enables data teams to automate data integration at scale with near-zero latency, and transform the raw data into analytics-ready state in a matter of minutes.

With this new partnership, Hevo Data will be available as part of Databricks Partner Connect. As a validated partner that’s natively integrated, Databricks customers can now easily access and deploy their ETL pipelines on Hevo Data right within Databricks.

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“We’re excited to build on our partnership with Hevo Data and bring another powerful lakehouse integration to our customers,” said Ariel Amster, Director of Strategic Technology Partners at Databricks. “With Partner Connect, customers can quickly discover and easily leverage Hevo Data directly from Databricks, taking advantage of a seamless connection that’s optimized for the lakehouse.”

“With this partnership with Databricks, we’re staying true to our goal of simplifying data-driven decisions for businesses,” added Manish Jethani, co-founder and CEO of Hevo Data. “We hope that we’re able to increase accessibility, reduce time-consuming and unnecessary maintenance, and enable innovation based on data for the growing Databricks customer base.”

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