The increased development of functionally diverse and highly specialized genome editors has created the need for comparative analytics tools that are able to profile the mutational outcomes, particularly rare and complex outcomes, to assess the editor's applicability to different domains. To address this need, we have developed Generalizable On-target activity ANAlyzer (GOANA), a high-throughput web-based software for determining editing efficiency and cataloguing rare outcomes from next-generation sequencing data. GOANA calculates mutation frequency and outcomes relative to a supplied control sample. It is scalable to thousands of target sites across the entire genome and is 4,000% faster than CRISPResso2. Mutations are reported on a "per-read" level rather than individually, enabling the identification of co-occurring mutations. GOANA is editor agnostic and can be applied to data generated from any targeted editing experiment, including base editors. Requiring only that control and treated reads are aligned to the same reference, GOANA can handle data from any library preparation method, including pooled amplicon and whole-genome sequencing. As a proof of principle, we analyze two large data sets of CRISPR-Cas9 and CRISPR-Cas12a editing, demonstrating the power of GOANA and highlighting several key differences between the two enzymes. GOANA is available for use at https://gt-scan.csiro.au/goana/ and as a command line tool from https://github.com/BauerLab/GOANA.