Objective: The objective of this study is to quantify the relationship between acute kidney injury (AKI) and alcohol use disorder (AUD), in terms of disease burden, mortality burden and disease progression. Methods: We used the University of California, San Francisco Medical Center in San Francisco, CA (UCSF) and Medical Information Mart for Intensive Care (MIMIC-III) databases to quantify AKI disease and mortality burden as well as AKI disease progression in the AUD and non-AUD subpopulations. We used the MIMIC-III dataset to compare two different methods of encoding AKI: ICD-9 codes, and the 2012 Kidney Disease: Improving Global Outcomes scheme (KDIGO). In addition to the AUD subpopulation (defined by AUD-related ICD-9 codes), we also present analysis for the hepatorenal syndrome (HRS) and alcohol-related cirrhosis subpopulations identified via ICD-9 coding. Results: In both the ICD-9 and KDIGO encodings of AKI, the AUD subpopulation had a higher prevalence of AKI (ICD-9: 48.59% vs. 29.99% AKI in the non-AUD subpopulations; KDIGO: 39.84% vs. 27.99%) in the MIMIC-III dataset. In the UCSF dataset, the AUD subpopulation also had a higher prevalence of AKI than the non-AUD subpopulation (ICD-9: 48.60% vs. 8.45%). The mortality rate of the subpopulation with both AKI and an AUD-related condition (AUD, HRS, or alcohol-related cirrhosis) was consistently higher than that of the subpopulation with only AKI in both datasets after adjusting for disease severity using two methods of severity estimation in the MIMIC-III dataset. Disease progression rates were similar for AUD and non-AUD subpopulations. Conclusions: Our work using the UCSF multi-ward academic hospital data and the MIMIC-III ICU dataset shows that the AUD patient subpopulation had a higher number of AKI patients than the non-AUD subpopulation, and that patients with both AKI and either AUD, HRS, or alcohol-related cirrhosis were shown to have higher rates of mortality than the non-AUD subpopulation with AKI. Trial Registration: Not applicable.