Today, businesses need more than just storage. They must process, analyze, and act on data in real-time. 

Whether you are a Fortune 25 bank that can dynamically adjust its fraud detection models in real-time, based on ongoing transactions across millions of accounts globally, or a healthcare provider making life-saving decisions using immediate insights from patient data, these are no longer futuristic use cases. This is where next-generation database architecture comes into play—designed not just to store but to power decision-making at unprecedented speed and scale.

Why now? Why can’t existing traditional infrastructures keep up?

In an era defined by AI, traditional architectures are not designed for the high concurrency, low latency, and massive data volumes AI brings. Many organizations are hitting a wall, finding their databases overwhelmed with massive data movements, leading to skyrocketing costs, lagging performance, and unsustainable energy consumption. As data grows exponentially, these costs don’t just add up—they start to bottom out your infrastructure.

In this session, we will learn how you balance speed and cost. How can you handle & process millions or even billions of data points in milliseconds without data movement & ballooning infrastructure costs? We explore how SingleStore, with its proprietary architecture built from the ground up for AI-scale workloads, leverages in-memory processing and distributed architecture and supports multimodel data types to ensure that your infrastructure evolves at the speed of business. We’ll also dive into examples of how innovative organizations have transformed their decision-making processes by switching to modern data platforms, gaining a competitive edge, delighting customers & unlocking new revenue streams.

The future is real-time, and the time to evolve is now.