Two full-scale slow sand filters (SSFs) were sampled periodically from April until November 2011 to study the spatial and temporal structures of the bacterial communities found in the filters. To monitor global changes in the microbial communities, DNA from sand samples taken at different depths and locations within the SSFs and at different filters ages was used for Illumina 16S rRNA gene sequencing. Additionally, 15 water quality parameters were monitored to assess filter performance, with functionally relevant microbial members being identified by using multivariate statistics. The bacterial diversity in the SSFs was found to be much larger than previously documented, with community composition being shaped by the characteristics of the SSFs (filter age and depth) and sampling characteristics (month, side, and distance from the influent and effluent pipes). We found that several key genera (Acidovorax, Halomonas, Sphingobium, and Sphingomonas) were associated with filter performance. In addition, at the whole-community level, a strong positive correlation was found between species evenness and filter performance. This study is the first to comprehensively characterize the microbial community of SSFs and link specific microbes to water quality parameters. In doing so, we reveal key patterns in microbial community structure that relate to overall community function.