class="knockout" style="margin-top: 0px;margin-bottom: 1px;font-size: 14px;line-height: 1.2;padding: 5px;padding-left: 20px;padding-right: 20px;font-weight: normal;">THANK YOU FOR SUBSCRIBING
Fremont, CA: Starburst raised $250 Million in Series D round of financing with a value of 3.35 billion dollars. Alkeon Capital led the fundraising round, including Altimeter and B Capital Group and current shareholders Andreessen Horowitz, Coatue Management, Index Ventures, and Salesforce Ventures. Starburst's total funding too far is 414 million dollars, as the firm expands operations to fulfill the industry's rising demand for speedier analytics on decentralized data.
Starburst is dismantling legacy hurdles erected by only a decades-old framework: the sole source of truth. Such data centralization technique, typically connected with data warehousing, necessitates data movement and preparation before being analyzed. Such an approach is costly, leads to data lock-in, and causes data teams to make sacrifices in how quickly they can evaluate the data they need to take active steps.
"Every organization has a top-down mandate to take more data-driven actions, but increases in data volumes have forced organizations to move, misplace and mismanage data, creating blind spots that can negatively impact decision-making," said Justin Borgman, CEO, and co-founder of Starburst. "Starburst streamlines data access and analytics across silos, clouds, and business lines, enabling organizations to become truly data-driven. Today's financing is a reflection of our continued growth and 'workhorse' mentality, from achieving profitability in our first two years of operation to tripling customer adoption in the past 12 months."
Starburst is enabling a new age of data analytics for businesses worldwide, including Zillow, Standard Chartered, and Carrefour Brazil. Starburst eliminates the need to transport data before evaluating it, reducing time to insight and enabling faster decisions. Fast SQL-based searches on data lakes or lakehouses to more complicated use cases combining data sets on a distributed Data Mesh architecture are among the core technology use cases.