starburstthe well funded data warehouse analytics service and data query engine based on the open-source Trino project, today announced it has acquired: Varada, a Tel Aviv-based startup focused on data lake analytics. By leveraging Varada’s proprietary indexing technology, enterprises can easily operationalize their data lakes, a capability that nicely extends Starburst’s query engine. This enables Starburst to better challenge companies like Snowflake and Databricks in the growing data analytics market.
“With the addition of Varada’s indexing technology, we can help data teams better serve the business by delivering the right data now. This powerful combination couldn’t come at a better time as an uncertain economy forces companies to re-evaluate their budgets as business demands only increase,” said Starburst CEO Justin Borgman in today’s announcement.
Similarly, Varada co-founder and VP of R&D Roman Vainbrand notes that the combined companies will be able to deliver “the best performance and cost benefits in the analytics query market, enabling organizations to accelerate time-to-insight while improving infrastructure operations.” optimization and investments.”
Varada’s engineering and product leadership teams will join Starburst and the two companies expect to be able to launch an integration between their products in the coming month, with general availability in the fall of 2022. The Starburst team believes the integrated product will allow its users will enable them to significantly reduce their cloud computing costs and improve their response times to queries by up to 7x.
The two companies did not disclose the price of the acquisition. Varada last raised a $12 million Series A round led by MizMaa Ventures in 2020. The company has gone through some leadership changes over the years, with co-founder and former CEO and CTO David Krakov leaving the company, for example. 2021 left. We haven’t heard much from Varada since the last funding round, but this is certainly an example of the data analytics market starting to consolidate as the underlying technologies mature, usage patterns crystallize and a small number of companies emerge as early winners.