Dremio Wins Best Big Data Startup in Second Annual Datanami Readers’ and Editors’ Choice Awards

MOUNTAIN VIEW, Calif., Sept. 25, 2017 -- Dremio, the self-service data company, announced today it has been recognized in the second annual Datanami Readers’ and Editors’ Choice Awards, presented during the Strata Data Conference 2017 NYC.  Dremio was awarded Reader’s Choice: Best Big Data Startup. Dremio provides the first Apache Arrow-based SQL execution engine, and leads the development of this project. Apache Arrow was also awarded Editors' Choice: Top 5 Open Source Projects to Watch. The list of winners were revealed on the Datanami website, located at www.datanami.com.

“Dremio provides a future proof strategy for data, allowing customers to choose the best tools for their analysts, and the right database technology for their apps, without compromising on their ability to leverage data to drive the business,” said Tomer Shiran, co-founder and CEO, Dremio. “We are honored that Datanami readers recognized our self-service data platform for its fundamentally new approach to data analytics. By working with all data sources and data science and BI tools, Dremio’s solution eliminates the need for traditional ETL, data warehouses, cubes, and aggregation tables, as well as the infrastructure, copies of data, and effort these systems entail.”

The Datanami Readers’ and Editors’ Choice Awards are determined through a nomination and voting process with input from the global Big Data community, as well as selections from the Datanami editors, to highlight key trends, shine a spotlight on technological breakthroughs, and capture a critical cross section of the state of the industry. These awards will be revealed each year to kick off the annual Strata Data Conference, which showcases data science, machine learning and analytics for business and technical professionals.

"Datanami is the premier news portal covering Big Data and advanced-scale analytics, and its readers are at the forefront of the global data science community. By taking part in our annual Readers’ Choice program, our readership has the privilege of honoring the top organizations making strides in Big Data today,” said Tom Tabor, CEO of Tabor Communications, publisher of Datanami.  "The Datanami Readers’ and Editors’ Choice Awards voice not only our support, but also the appreciation from the community at large, and we couldn’t be more proud to celebrate these organizations and their accomplishments. Our congratulations go out to all the winners.”

More information on these awards can be found at the Datanami website (www.datanami.com) or on Twitter through the following hashtag: #DatanamiAwards.

About Datanami
Datanami is one of the premier online portals covering big data, produced by Tabor Communications, Inc. (TCI) a leading international media, advertising and communications company dedicated to covering advance computing technologies for science, research and business. Datanami is a premier online portal covering big data. It is produced by Tabor Communications, Inc. Receive a complimentary subscription to the weekly Datanami e-newsletter by visiting datanami.com/subscribe. View daily news at www.datanami.com

About Dremio
Dremio reimagines analytics for modern data. Created by veterans of open source and big data technologies, Dremio is a fundamentally new approach that dramatically simplifies and accelerates time to insight. Dremio empowers business users to curate precisely the data they need, from any data source, then accelerate analytical processing for BI tools, machine learning, data science, and SQL clients. Dremio starts to deliver value in minutes, and learns from your data and queries, making your data engineers, analysts, and data scientists more productive.​ For more information, visit www.dremio.com.

Founded in 2015, Dremio is headquartered in Mountain View, CA. Investors include Lightspeed Venture Partners and Redpoint. Connect with Dremio on GitHub, LinkedIn, Twitter and Facebook

Media Contact:
Kim Pegnato
Winkowski Public Relations
(781) 620-0016
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