A wide range of analytic and data sharing options are available in non-experimental multi-database studies designed to assess the real-world benefits and risks of medical products. Researchers often consider six scientific domains when choosing among these options - study design, exposure type, outcome type, covariate summarization technique, covariate adjustment method, and data sharing approach. This article reviews available analytic and data sharing options and discuss key scientific and practical considerations when choosing among these options in multi-database studies of comparative effectiveness and safety of medical products. The scientific considerations must be balanced against what the data-contributing sites are able or willing to share. While pooling of person-level datasets remains the most familiar and analytically flexible approach, newer analytic and data sharing approaches that share less granular summary-level information may be equally valid and preferred in some multi-database studies, especially when sharing of person-level data is challenging or infeasible.