The impact of ammonia on anaerobic digestion performance and microbial dynamics has been extensively studied, but the concurrent effect of anions brought by ammonium salt should not be neglected. This paper studied this effect using metabolomics and a time-course statistical framework. Metabolomics provides novel perspectives to study microbial processes and facilitates a more profound understanding at the metabolic level. The advanced statistical framework enables deciphering the complexity of large metabolomics data sets. More specifically, a series of lab-scale batch reactors were set up with different ammonia sources added. Samples of nine time points over the degradation were analyzed with liquid chromatography-mass spectrometry. A filtering procedure was applied to select the promising metabolomic peaks from 1262 peaks, followed by modeling their intensities across time. The metabolomic peaks with similar time profiles were clustered, evidencing the correlation of different biological processes. Differential analysis was performed to seek the differences in metabolite dynamics caused by different anions. Finally, tandem mass spectrometry and metabolite annotation provided further information on the molecular structure and possible metabolic pathways. For example, the consumption of 5-aminovaleric acid, a short-chain fatty acid obtained from l-lysine degradation, was slowed down by phosphates. Overall, by investigating the effect of anions on anaerobic digestion, our study demonstrated the effectiveness of metabolomics in providing detailed information in a set of samples from different experimental conditions. With the statistical framework, the approach enables capturing subtle differences in metabolite dynamics between samples while accounting for the differences caused by time variations.