The ideal database for AI agents doesn't exist yet, says Percona CEO
Iterative workloads caught vendors off guard, but requirements for a clean-slate solution remain unclear
Peter Farkas, CEO of Percona, argues that no existing database is ideal for AI agents, as the industry is unprepared for the unique workloads they generate. During an interview at the Percona Live event in Amsterdam, Farkas highlighted that AI introduces iteration-focused workloads where an agent might make 150 attempts before a person selects the best result.
He noted that current databases were not designed for such intensive testing, and thus no single option is currently suitable. Farkas emphasized that organizations must choose technology capable of handling these demanding workloads, while acknowledging that the optimal solution does not yet exist due to the rapid pace of AI development.
He cautioned against rebranding existing databases as AI databases and stressed that Percona is exploring ways to contribute to this emerging field, but not by simply adopting a vendor lock-in approach.
Written by urgent.news from The Register Science's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
