Starburst + AI

I’ve always believed in technology that solves real business problems. Over the years, as the importance of data has expanded, these opportunities have expanded as well. At the outset of the big data era, I quickly grasped the business value of making large-scale data more accessible to all businesses. Trino is rooted in this problem, but at the time, only companies at the scale of Facebook or Netflix had the resources to create solutions. 

I wanted to change that. 

Starburst is a testament to this conviction–the belief that every company should benefit from data. Today, Starburst Galaxy makes using Trino easier than ever before. We help companies build a foundation for their data architecture wherever it lives, regardless of data structure, and secure it using strong data governance and data management. Meanwhile, our efforts around Apache Iceberg have given rise to the Icehouse data architecture, pairing Trino + Iceberg and helping customers to gain business value from their data in new ways. 

Follow the data (architecture)

But data never stands still, and today there are new frontiers of value, particularly in the area of Artificial Intelligence (AI). Together, our industry and our world are once again at a turning point, and Starburst is turning with it.

Today, our customers use Starburst to prepare the foundation of their data stack. This foundation is often used for analytics, but it is increasingly being used for AI too, where we have become part of an emerging AI data stack. To me, this evolution feels natural. At their heart, both analytics and AI are just two halves of the same data problem. They both seek to turn raw data into insights that solve real business problems. If big data’s answer to this problem was the creation of large-scale systems of record, AI’s solution is the emergence of systems of intelligence. 

In this sense, Starburst is fast becoming a foundational layer for AI data architecture. 

AI unlocks the value of customer data like never before

AI changes the foundational value of data for our customers–and it’s already happening. Today, hundreds of customers use Starburst every day to make all their data architecture AI-ready. Tomorrow, it will be thousands. 

While those solutions are as varied as the companies themselves, they all use Starburst to provide the data architecture needed for AI. They operate in the cloud, on-premises, and increasingly, through a mixture of both using the hybrid lakehouse model. Most importantly of all, they unlock that data no matter its data structure and secure it using an easy, all-in-one solution. These companies operate across every industry, every sector, and around the world. 

Data architecture serving AI is growing rapidly

This trend is only going to increase. Today, AI is inseparable from data. In fact, if we look at key milestones in the evolution of AI, the importance of the data itself is center stage. This is because modern AI relies on probabilistic architectures where more data beats better algorithms. For AI to advance, the data foundation that it’s built upon has to be broad–the bigger, the better. 

What does this mean for Starburst? It means that AI needs a scalable data architecture that accesses data from multiple sources in multiple formats while governing it securely. Starburst is this data architecture, and it’s helping to remove bottlenecks in AI data workflows, exactly like it helped remove them in analytics. 

At the same time, scale alone isn’t enough. As we’ll discuss, limitations on general-purpose LLMs mean that, in many cases, better data beats more data. Context is king, and methods like Retrieval-Augmented Generation (RAG) help bridge that gap.

Importantly, this is happening now—not tomorrow or in some distant future. It’s happening today. In essence, a critical mass has been reached. This epochal shift has made data and AI inseparable. 

Beyond analytics 

The truth is, there’s more to data than just analytics. You just need to follow the data. 

The AI era is here, and every passing month proves that this trend is not just the latest fad. It is the road that businesses are actively taking to solve their business problem. 

Something else is interesting, too. Analytics and AI both rely on data. This approach isn’t something that happened overnight. In fact, it underpins everything I said previously about the convergence between the needs of Analytics and AI. Today, answering the question, ” What can your data do for you?” increasingly means going beyond analytics. It means AI.  

Starburst + AI

That’s why Starburst is announcing an expansion of our AI foundation, developing a suite of AI accelerators to help our customers get the most value from their data–whether that means analytics or AI. 

AI is happening today

This isn’t just something happening tomorrow—it’s happening today. Our customers are already using Starburst for AI, and this usage is only going to expand as AI workloads increasingly shape the future direction of data volume. 

What we’re seeing is a world where data architecture is reaching a new phase–a world where the same data lakehouse architecture that helps drive analytics to new heights also feeds generative AI (GenAI) and machine learning (ML) models. 

Starburst and AI architecture

To meet this new landscape, Starburst is evolving to capture the growing demand for data architecture capable of serving AI workloads. This effort builds on top of our core Icehouse architecture, to include a suite of AI accelerators that speed up our customers’ ability to move from development to deployment–to go from AI proof of concept (POC) to full-scale productive intelligence. 

These include workload optimizations, streaming ingestion, file load ingestion, improved AI governance support, and features supporting RAG architecture. Our customers are already using Starburst to power the foundation of their AI architecture, including RAG architecture and AI applications, and this next wave of development will consolidate and accelerate that momentum. 

Data to the power of AI 

There is no AI without data. Not a single AI model operates without data to train on, and the continued flow of data into models allows them to grow. In this sense, you can think of data as the foundation. Not just the foundation of analytics but also the foundation of AI. What you build on top of it depends on your ability to build that foundation in a secure, reliable, and predictable way. 

Starburst is already the foundation for data analytics, and that role is growing with each passing day.  Increasingly, it is also the foundation for AI. In both cases, the role we play is similar. At its heart, Starburst is an engine. That engine could power your analytics data stack, but it could also power your AI or ML data stack. It could power the data stack that drives your BI dashboard, your data application, or your AI model. In this sense, we’re both an analytics SQL query engine and an AI query engine. 

The same things that make an analytics data stack successful also make an AI data stack successful. In both cases, data needs to be accessible, organized, and governed. With AI growing so fast, there is a huge and growing demand to build data foundations in every business, whether they use AI today or are thinking of adopting it tomorrow. 

What data analytics and AI have in common

The truth is that analytics and AI have a lot in common. They both rely on data, and both require a firm data foundation to be successful. 

As businesses continue to push forward their analytics projects while rolling out new AI projects, the need for a foundation has never been greater. Both ventures thrive on high-quality, collaborative, and well-governed data, making data platforms like Starburst foundational for enabling secure and impactful AI-driven innovation. 

You can think of it like this: If AI is the jet engine driving innovation, data is the meticulously refined fuel that powers it. Without accessible, collaborative, and well-governed data, the engine sputters and fails to perform. Together, these three characteristics form the foundations of AI. 

Strong AI architecture begins with data architecture  

What we’re witnessing is nothing short of historic. Data architecture has always had a huge impact on the success of data analytics, which is exactly why getting this technology right has meant the difference between success and failure throughout the history of big data. 

Data architecture + AI

With the shift towards AI, data architecture is once again in focus. Just like before, a good foundation for this data architecture is essential.

Without data, you don’t have anything. That’s true of data analytics, and it’s also true of AI. And while AI expands the possibility of business value in new and exciting ways, achieving those objectives remains rooted in business value. 

Starburst: One foundation for all your data

That’s why seeing Starburst as both an analytics and AI company makes sense. We’re just going where the data is to help everyone benefit from data. 

This has always been the Starburst mission, and it always will be. One way to access all your data; one place for analytics; and one place for AI.

One foundation for all your data.