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Starburst Achieves Google Cloud Ready - BigQuery Designation
  • India - English


News provided by

Starburst Data

Mar 29, 2023, 09:00 ET

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Key integrations with Google Cloud enable customers to analyze data across sources

BOSTON, March 29, 2023 /PRNewswire/ -- Starburst, the analytics anywhere company, today announced that it has successfully achieved Google Cloud Ready - BigQuery designation. Its latest innovations with Google Cloud bring the power of Starburst to native Google Cloud services Dataplex and BigQuery.

Google Cloud Ready - BigQuery is a partner integration validation program that intends to increase the customer confidence in partner integrations into BigQuery. As part of this initiative, Google Cloud engineering teams validate partner integrations into BigQuery in a three phase process - Run a series of data integration tests and compare results against benchmarks, work closely with partners to fill any gaps and refine documentation for our mutual customers.

By earning this designation, Starburst has proven its products have met a core set of functional and interoperability requirements when integrating with BigQuery. This designation enables customers to discover and have confidence that the Starburst products they use today work well with BigQuery or save time on evaluating them, if not already using. Being part of the program, Starburst gets more opportunities to collaborate closely with Google Cloud partner engineering and BigQuery teams to develop joint roadmaps. Starburst's new integrations with Google Cloud include:

  • Dataplex and data products powered by Starburst – With this new integration, Starburst functions as a distributed query engine within Dataplex, making metadata associated with other data sources accessible within the Dataplex catalog and giving companies the opportunity to build and maintain a true data mesh that encompasses all enterprise datasets, including those outside Google Cloud.
  • BigQuery plus Starburst – The Starburst integration with BigQuery extends its data analytics capabilities, enabling BigQuery to read datasets from other clouds and on-prem sources. As a result, Google Cloud can broaden the reach of its native tools and provide its customers with access to more data, and the ability to extend their data mesh and, ultimately, discover business insights faster.

"We're excited to validate Starburst's achievement of the Google Cloud Ready - BigQuery designation," said Ritika Suri, Director, Technology Partnerships at Google Cloud. "Through our partnership, Starburst continues to extend its data analytics capabilities with BigQuery by delivering strong customer value and experiences."

"As companies continue to generate large amounts of data, it's important to have a distributed query engine that allows organizations to analyze their data regardless of where it lives," said Ali Huselid, SVP of Product, Starburst. "Starburst is excited about this designation and about integrating with BigQuery and Dataplex to provide enhanced access to data and discover faster business insights."

To learn more about Starburst's integrations with Dataplex and BigQuery visit our blog post. To learn more about Starburst, please visit our website: www.starburst.io/.

About Starburst
Starburst is the analytics engine for all your data. We provide the fastest, most efficient analytics engine for your data warehouse, data lake, or data mesh. We unlock the value of distributed data by making it fast and easy to access, no matter where it lives. Starburst queries data across any database, making it instantly actionable for data-driven organizations. With Starburst, teams can lower the total cost of their infrastructure and analytics investments, prevent vendor lock-in, and use the existing tools that work for their business. Trusted by companies like Apache Corporation, Comcast, Doordash, FINRA, Priceline, and VMware, Starburst helps companies make better decisions faster on all data.

For more information, press only:
Tucker Hallowell
Inkhouse
[email protected]
339-368-2290

SOURCE Starburst Data

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