The increasing availability of digital health data heralds a new era in transfusion research. These data can be assembled into large databases integrating donor, component, and recipient information, enabling studies across the transfusion continuum ("vein-to-vein"). However, establishing and maintaining such databases requires significant resources, and few investigators currently have access to them. To guide future efforts, we reviewed published vein-to-vein databases, focusing on their research use, data scope, limitations, and technical design considerations. Several studies have used vein-to-vein databases to examine determinants of transfusion effectiveness and safety. These studies would benefit from more international collaboration to explore variation and validate findings. Such collaborations could be facilitated through public protocol and data sharing, adherence to recognized standards, or the development of new, widely accepted ones. Investigators who develop vein-to-vein databases must consider the need for data quality and validation checks. Where feasible, investigators should also consider linking vein-to-vein data with prospective cohort studies that include donation and recipient biospecimens to evaluate novel or emerging exposures and explore epidemiological and mechanistic associations. They should also recognize the limitations of vein-to-vein database studies, including residual confounding, data quality issues, and missing data due to outpatient transfusions, home transfusions, or patients without health insurance. Despite these limitations, vein-to-vein databases should be developed, enhanced, and leveraged to provide insights into transfusion efficacy and support pragmatic or emulated randomized controlled trials (RCTs), especially where traditional RCTs are not feasible (eg, platelet thresholds to prevent bleeding complications after lumbar puncture).