Mikio L. Braun taking a look at using a database approach vs stream processing for real-time stream processing:
Putting all your data into a database is problematic because the data steadily grows and computing statistics based on the data is too slow. You also don’t really need to keep all your data at hand to have an analysis of the current state of the stream.
Stream processing, on the other hand, is a nice tool to scale your computations, but it doesn’t deal well with peak volumes, and depending on how you persist your data, you run into the same scaling issues as the database centric approach.
The problem space Mikio is looking at is aggregation. Imagine the complexity of real-time stream augmentation (one that doesn’t necessarily grow linearly with the input) .
Original title and link: Real-Time Stream Processing: A Look at Two Approaches ( ©myNoSQL)