Varada and Starburst Announce Strategic Partnership to Help Enterprises Accelerate Data Lake Adoption

Companies to collaborate on bringing Varada's indexing and query acceleration technology to Starburst's robust support of data sources and enterprise-grade features.

TEL AVIV, Israel (PRWEB) March 17, 2021

Varada, the data lake query acceleration innovator, today announced a partnership with Starburst, the analytics anywhere company to leverage both companies' technical strengths to bring data and analytics teams new solutions that improve the economics and performance of data lake-based analytics.

Starburst, which recently secured $100M in Series C funding, offers a common query tool, abstracted from the systems that store data, and enables to run analytics on data where it lives. Varada, based on its dynamic and adaptive indexing technology, delivers dramatic acceleration for data lake queries running on thousands of dimensions. Varada offers a smart and autonomous indexing technology that leverages machine learning capabilities to dynamically accelerate queries to meet evolving business requirements.

Starburst and Varada technologies together deliver a set of synergistic capabilities that offer the high performance of data warehouses also for queries running on massive data lakes. Starburst brings easy access to many data sources, a scalable SQL engine and a rich set of powerful enterprise features. Varada offers the power of indexing for query acceleration and zero time-to-insights. Both companies' technologies deliver the flexibility to monetize data directly on top of the cloud data lake, simplifying deployment and operations, reducing the cost, control, and security issues of cloning data into proprietary environments.

"The strengths of Varada and Starburst complement each other almost perfectly," said Eran Vanounou, CEO of Varada. "Starburst's scalable query engine, high performance, easy access to any data source and powerful set of enterprise features fit perfectly with our indexing technology and seamless integration with Starburst. And since both of us are built to support Trino and operate directly atop the data lake, we're architecturally aligned. It's a perfect fit for customers who need speed, security and efficiency as they scale out their data lake analytics plans across the entire organization."

"The data lake is a fundamentally transformative change in data architecture for enterprises that have relied on data warehouses multiple decades," said Justin Borgman, chairman & CEO of Starburst. "This shift means that organizations can finally—and very easily—run analytics projects on any data set and intelligently monetize all their data to gain a competitive edge. This shift, however, requires new tools that are built for a data-lake-native world. That's what we've created, and that's what we're working with Varada to perfect."

About Varada
The Varada mission is to enable data practitioners to go beyond the traditional limitations imposed by data infrastructure and instead zero in on the data and answers they need—with complete control over performance, cost and flexibility. In Varada's world of big data, every query can find its optimal plan, with no prior preparation and no bottlenecks, providing consistent performance at a petabyte scale. Varada was founded by veterans of the Dell EMC XtremIO core team, and is dedicated to leveraging the data lake architecture to take on the challenge of data and business agility. Varada has been recognized in the Cool Vendors in Data Management report by Gartner, Inc. For more information, visit: https://varada.io/

About Starburst
Starburst unlocks the value of data by making it fast and easy to access anywhere. Starburst queries data across any database, making it instantly actionable for organizations. With Starburst, teams can lower the total cost of their infrastructure and analytics investments, prevent vendor lock-in, and use the tools that work best for their business. Trusted by companies like Zalando, FINRA and Condé Nast, Starburst helps companies make better decisions faster on all data.

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