  This decade, the Square Kilometre Array (SKA) will perform its first
observations. Preparations for building dishes, antennas, correlators and
infrastructure are well underway. Concurrently, software for the processing of
SKA observations is developed at a number of levels. At a more basic level
there are the telescope monitoring and control systems and also the correlator
software. On top of that, in order to deliver science ready data products,
software pipelines are needed for radio frequency interference (RFI)
mitigation, averaging, calibration and imaging. Here, we focus on the SAGECal
calibration package, in particular on the times needed to obtain calibration
solutions. This is an important aspect, since this package is now used for the
Epoch of Reionization (EoR) Key Science Project of LOFAR, but will also have to
run optimally on SKA1 LOW. In terms of number of stations used for observing
this amounts to a factor 10 increase, from 51 to 512 stations. Consequentially,
the disk space needed to store an observation will increase by a factor 100,
provided the number of frequency channels remains the same. In this paper we
investigate the scaling behaviour of SAGECal, whose runtimes should ideally
scale linearly with the number of stations. We also explain the algorithms
inside SAGECal and use them to explain its scaling behaviour.
