To start, Justin, can you share a bit about your journey as a software engineer and how those early experiences influenced your path to founding Starburst?

My background as a software engineer gave me firsthand insight into the complexities of building technology that solves real-world problems. Early in my career, I founded Hadapt, which introduced “SQL on Hadoop,” transforming Hadoop into a tool for analytics and laying the groundwork for today’s Lakehouse architecture. After Hadapt’s acquisition by Teradata, I witnessed the growing inefficiencies of traditional data warehouses as businesses grappled with massive data growth and cloud adoption. Discovering Trino, an open-source distributed SQL engine, inspired me to co-found Starburst with a mission to enable efficient, scalable data analytics without the constraints of proprietary systems.

Cost and efficiency are critical in enterprise AI. Could you elaborate on how Starburst’s technology enables businesses to reduce AI compute costs by up to 50% without compromising on performance or scalability?

Starburst reduces AI compute costs by up to 30 – 50% by streamlining data processing and eliminating the need for data duplication and movement, which are major drivers of infrastructure expenses. Our platform allows businesses to query, transform, and analyze data directly where it resides, significantly cutting costs without sacrificing performance or scalability.

Security and compliance are paramount in AI-driven operations. How does Starburst ensure secure and governed interactions between enterprise data and AI models?

Starburst ensures secure and governed interactions between enterprise data and AI models through robust governance and access controls. Our platform enforces compliance with industry regulations like GDPR, providing full visibility into data usage and access. By enabling role-based permissions, Starburst safeguards sensitive information while ensuring only authorized users can interact with critical datasets.

Adapting to AI’s rapid evolution is a pressing concern for businesses. How does Starburst’s data platform for AI help organizations future-proof their AI investments and prepare for emerging trends?

Starburst’s data platform for data apps and AI future-proofs AI investments by enabling businesses to scale seamlessly as AI evolves. Our ability to query data across multiple sources without moving it allows organizations to integrate emerging technologies and trends like AI and machine learning without costly infrastructure changes. By combining the flexibility of a data lake with the performance of a warehouse, Starburst ensures businesses can easily adapt to increasing data complexity and growing AI demands. This architecture supports real-time analytics, enabling enterprises to stay agile, scale efficiently, and leverage data for new AI-driven innovations as they emerge.

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