CedarDB wants one database to handle both transactions and analytics, as AI agents raise the stakes

CedarDB is building a database engine designed to handle both operational transactions and analytical workloads, rather than forcing companies to separate the two. The company says this unified approach is becoming more relevant as agentic AI systems need fast access to fresh, reliable data.

The push toward hybrid databases reflects a broader shift away from fragmented data stacks and batch-based analytics. As AI agents begin making decisions and taking actions in real time, demand will grow for systems that combine low-latency operations with deep analytical capabilities.