1 year ago

While the term “real time” can be used as a marketing spin in some cases, there are genuine technical and functional differences between real-time analytic databases and conventional analytic databases. Real-time analytic databases (aka streaming databases) are a distinct category of https://thenewstack.io/more-database-analytics-workloads-ran-on-kubernetes-in-2022/ that are optimized for processing and analyzing high-volume, high-velocity data in near real time.

The “steelman” argument against the notion that real-time analytic databases are fundamentally different from conventional analytic databases is that real-time analytic databases are simply an extension of the traditional analytic database paradigm with added real-time capabilities.

Proponents of this argument point out that both real-time analytic databases and conventional analytic databases are designed to store and analyze large volumes of data and the underlying principles of data storage, indexing and querying are largely the same in both cases.

To make the case for real-time analytic databases being a distinct category, consider the below framework based on data latency and query latency.