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Sediment DNA (sedDNA) analyses are rapidly emerging as powerful tools for the reconstruction of environmental and evolutionary change. While there are an increasing number of studies using molecular genetic approaches to track changes over time, few studies have compared the coherence between quantitative polymerase chain reaction (PCR) methods and metabarcoding techniques. Primer specificity, bioinformatic analyses, and PCR inhibitors in sediments could affect the quantitative data obtained from these approaches. We compared the performance of droplet digital polymerase chain reaction (ddPCR) and high-throughput sequencing (HTS) for the quantification of target genes of cyanobacteria in lake sediments and tested whether the two techniques similarly reveal expected patterns through time. Absolute concentrations of cyanobacterial 16S rRNA genes were compared between ddPCR and HTS using dated sediment cores collected from two experimental (Lake 227, fertilized since 1969 and Lake 223, acidified from 1976 to 1983) and two reference lakes (Lakes 224 and 442) in the Experimental Lakes Area (ELA), Canada. Relative abundances of Microcystis 16S rRNA (MICR) genes were also compared between the two methods. Moderate to strong positive correlations were found between the molecular approaches among all four cores but results from ddPCR were more consistent with the known history of lake manipulations. A 100-fold increase in ddPCR estimates of cyanobacterial gene abundance beginning in ~1968 occurred in Lake 227, in keeping with experimental addition of nutrients and increase in planktonic cyanobacteria. In contrast, no significant rise in cyanobacterial abundance associated with lake fertilization was observed with HTS. Relative abundances of Microcystis between the two techniques showed moderate to strong levels of coherence in top intervals of the sediment cores. Both ddPCR and HTS approaches are suitable for sedDNA analysis, but studies aiming to quantify absolute abundances from complex environments should consider using ddPCR due to its high tolerance to PCR inhibitors.