Time-domain astronomy is becoming a fundamental aspect of the next generation of astronomical instruments.
The timing properties will revolutionise the studies of all kinds of astronomical objects. Consequetially, the
huge complex data volumes and high cadences of these facilities will force us to overhaul and extend current
software solutions. LOFAR, laying the groundwork for this, will produce a continuously updated spectral light-curve catalogue of all detected sources, with real-time capabilities to cope with the growth of 50 - 100TB/yr,
making it the largest dynamic astronomical catalogue. Automated pipelines use the column-store MonetDB as
their key component. We exploit SciLens, a 300+ node, 4-tier locally distributed cluster focussed on massive
I/O. Introduction of the new array-based query language, SciQL, simplifies data exploration and mining. I
will demonstrate how MonetDB/SQL & SciQL on its SciLens platform manages the millions of lightcurves for
LOFAR. Initial benchmark results confirm the linear scale-up performance over tens of TBs using tens of nodes.