BurstWere well funded A data warehouse analytics service and data query engine based on the open-source Trino project today announced that it has acquired Varad, a Tel Aviv-based startup focused on data lake analytics. Using Varda’s proprietary indexing technology, enterprises can easily operate their own data lakes, a capability that neatly extends Starburst’s query engine. This, Starburst argues, will allow it to better challenge the likes of Snowflake and Databricks in the growing data analytics market.
“With the addition of Varda’s indexing technology, we can help data teams better serve businesses, providing the right data right now. This powerful combination couldn’t have come at a better time when an uncertain economy is giving companies a better chance of their business.” This is forcing a re-evaluation of the budget, as business demand only grows,” explains Starburst CEO Justin Borgman in today’s announcement.
Similarly, Varda co-founder and VP of R&D Roman Weinbrand noted that the combined companies “will be able to deliver the best performance and cost advantage in the analytics query market, helping organizations accelerate time-to-time insights.” , while there will be optimization of infrastructure operations and investments.”
Varda’s engineering and product leadership team will join Starburst and the two companies expect to be able to begin integration between their products next month, with general availability by 2022. The Starburst team believes the integrated product will allow its users to significantly. Reduce their cloud computing costs and improve their query response times by up to 7x.
The two companies did not disclose the acquisition price. Varda last raised a $12 million Series A round led by Mizma Ventures in 2020. For example, the company’s co-founder and former CEO and CTO David Krakow left the company in late 2021. We haven’t heard much from Varda since its last funding round, but it’s certainly an example of a data analytics market that has begun to consolidate as the underlying technologies mature, usage patterns crystallize and Very few companies emerge as early winners.