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Coming high-cadence wide-field optical telescopes will image hundreds ofthousands of sources per minute. Besides inspecting the near real-time datastreams for transient and variability events, the accumulated data archive is awealthy laboratory for making complementary scientific discoveries.  The goal of this work is to optimise column-oriented database techniques toenable the construction of a full-source and light-curve database forlarge-scale surveys, that is accessible by the astronomical community.  We adopted LOFAR's Transients Pipeline as the baseline and modified it toenable the processing of optical images that have much higher source densities.The pipeline adds new source lists to the archive database, whilecross-matching them with the known cataloged sources in order to build a fulllight-curve archive. We investigated several techniques of indexing andpartitioning the largest tables, allowing for faster positional source look-upsin the cross matching algorithms. We monitored all query run times in long-termpipeline runs where we processed a subset of IPHAS data that have image sourcedensity peaks over $170,000$ per field of view ($500,000$ deg$^{-2}$).  Our analysis demonstrates that horizontal table partitions of declinationwidths of one-degree control the query run times. Usage of an index strategywhere the partitions are densily sorted according to source declination yieldsanother improvement. Most queries run in sublinear time and a few (<20%) run inlinear time, because of dependencies on input source-list and result-set size.We observed that for this logical database partitioning schema the limitingcadence the pipeline achieved with processing IPHAS data is 25 seconds.

Fast in-database cross-matching of high-cadence, high-density source lists with an up-to-date sky model