Stateful Stream Processing

Stateful stream processing involves continuously analyzing data that flows in real-time while maintaining memory of past information. Unlike simple processing that treats each piece of data independently, stateful processing tracks previous events or data points to make informed decisions. For example, it can count how many times a user visits a website or detect patterns over time. This approach enables systems to respond dynamically based on ongoing context, supporting applications like fraud detection, real-time analytics, and personalized recommendations. It balances the immediacy of real-time data with the need to remember and utilize historical information for smarter insights.