Part 3/10:
Looking back fifteen years, most systems were designed based on static data and periodic updates. The dominant infrastructure comprised traditional databases and batch processing systems that gathered, processed, and stored data at scheduled intervals. These architectures were sufficient at the time but are increasingly inadequate in the face of modern, demanding use cases that require continuous data flows.
The limitations of legacy systems—such as latency, batch delays, and inability to handle high-throughput real-time data—prompted the industry to creative new solutions. The need for systems capable of immediate processing and response became apparent, giving rise to real-time data streaming technologies.