Yukon handles 1M events per second with agent-ready tables

Streaming massive amounts of real-time data is hard enough, but now data platforms also have to worry about vendor lock-in and AI agent accessibility.

Surviving the stream and prepping for agents

During a one-hour benchmark conducted by Eon, Yukon was tasked with ingesting 1 million streaming events per second. The requirement was simple but demanding: keep tables less than two minutes behind real time. Yukon met the bar.

Instead of locking data behind proprietary walls, Yukon saves tables in an open format directly inside your AWS or Google Cloud account. Even if you walk away from Yukon later, your other data tools can still read the files without friction.

It also adds an agent-friendly twist. Yukon keeps notes on what each table contains and tracks what changed over time. That means an AI agent looking for last week's updates can just check the notes rather than scanning the entire table from scratch.

Why it matters

Handling a million events per second with low latency is solid table stakes, but the real draw here is how Yukon balances data ownership with AI ergonomics. Storing open formats in your own cloud eliminates vendor lock-in, while logging change summaries saves serious compute and token costs when agents inspect data. We think baking agent-specific read patterns directly into core data infrastructure will soon become standard practice.