This study compared the efficiency of geostatistical digital soil mapping (DSM) with conventional soil mapping (CSM) for updating soil class and property maps of a cultivated peatland in the Netherlands. For digital soil class mapping, the generalized linear geostatistical model was used. Digital mapping of the soil organic matter (SOM) content and peat thickness was done by universal kriging. The conventional soil class map was created by free survey, while the property maps were created with the representative profile description (RPD) and map unit means (MUM) methods. For each method, we computed the effort invested in the mapping in terms of the sampling and cost densities. The accuracies of the created soil maps were estimated from independent probability sample data. The results showed that for DSM, the cost density could be reduced by a factor of three compared with CSM without compromising accuracy. The map purity of both maps was around 55%. For conventional soil property mapping, the MUM maps were more accurate than the RPD maps. For SOM, CSM-MUM (RMSE 7.5%) performed better than DSM (RMSE 12.1%), although accuracy differences were not significant. For peat thickness, DSM (RMSE 23.3 cm) performed slightly better than CSM-MUM (RMSE 24.9 cm). Despite the differences in accuracy being small, the digital soil property maps were produced more efficiently. The cost density was a factor of 3.5 smaller. We conclude that for updating conventional soil maps in the Dutch peatlands, geostatistical DSM can be more efficient, although not necessarily more accurate, than CSM.