Real-Time Memory
Real-Time Memory refers to a system architecture where data is processed and accessed with extremely low latency, often residing entirely or partially in high-speed volatile memory (like RAM or specialized caches) rather than slower persistent storage (like SSDs or HDDs).
This capability allows applications to react to incoming data streams or user inputs almost instantaneously, making the system's response time negligible.
In today's data-intensive landscape, delays are costly. Real-Time Memory is critical for applications requiring immediate feedback, such as high-frequency trading, live fraud detection, and interactive AI agents. It shifts the bottleneck from I/O operations to pure computational speed.
The core mechanism involves keeping the working dataset in memory. Instead of executing a query that requires fetching data from disk, the system queries the memory structure directly. Advanced implementations often use specialized data structures optimized for rapid lookup and update, sometimes involving techniques like stream processing engines.
