Alteryx, on Wednesday, announced an enhanced partnership with Databricks that is designed to help Alteryx users merge their industry expertise with Databricks’ data science and generative AI capabilities. The partnership includes an integration with the Databricks Partner Connect marketplace, which gives existing Databricks customers access to a free trial of the Alteryx Analytics Cloud.
The integration will allow customers to seamlessly combine Databricks’ capabilities with Alteryx data and applications with just a few clicks, according to Alteryx. Headquartered in Irvine, California, Alteryx is a data management and analytics vendor that focuses on empowering business users to work with data.
Databricks, based in San Francisco, is known for pioneering the data lakehouse architecture and providing AI-driven data infrastructure tools for data experts. The company has recently shifted its focus to generative AI, with recent acquisitions and new product offerings reflecting this emphasis.
The partnership between Alteryx and Databricks is seen as a logical fit, as it brings together two different audiences and provides them with new capabilities, according to David Menninger, an analyst at ISG’s Ventana Research. Alteryx also has partnerships with Snowflake, AWS, Google, and Microsoft, while Databricks has partnerships with various data preparation and analytics vendors.
This expanded partnership builds on the companies’ existing relationship and includes new integrations that enable joint users to execute Alteryx Designer workflows with Databricks SQL and SQL Serverless, offering potential cost savings and operational benefits.
The partnership with Databricks also represents a shift in the nature of the collaboration between the vendors, with the integration now extending beyond Alteryx users accessing Databricks capabilities to a more bi-directional integration.
Moving forward, Alteryx and Databricks plan to continue expanding their partnership and developing further integrations, with a focus on incorporating generative AI capabilities and better integrating with data catalogs to improve data lineage and quality.