Temperature-aware Data Management in Polypheny-DB (Master Project, Finished)


Marc Hennemann


In the data management community it is common practice to describe the access frequency of a certain data set by a “temperature”. Hot means that the data is currently very frequently accessed while cold means that it hasn’t been accessed for a long time. In between, there can be multiple nuances of warm.

Multi-temperature data management refers to the approach of storing hot data on fast (and expensive), warm data on a slightly slower and cold data on slow, but also very cheap

The goal of this project is to

Start / End Dates

2021/02/08 - 2021/07/25


Research Topics