Cost and schedule overruns are common in the procurement of large-scale defense acquisition programs. Current work focuses on identifying the root causes of cost growth and schedule delays in the defense acquisition programs. There is need for a mix of quantitative and qualitative analysis of cost and schedule overruns which takes into account program factor such as, technology maturity, design maturity, initial acquisition time, and program complexity. Such analysis requires an easy to access database for program-specific data about how an acquisition programs’ technical and financial characteristics vary over the time. To fulfill this need, the objective of this paper is twofold: (i) to develop a database of major US defense weapons programs which includes details of the technical and financial characteristics and how they vary over time, and (ii) to test various hypotheses about the interdependence of such characteristics using the collected data. To achieve the objective, we use a mixed-method analysis on schedule and cost growth data available in the U.S. Government Accountability Office’s (GAO’s) defense acquisitions annual assessments during the period 2003–2017. We extracted both analytical and textual data from original reports into Excel files and further created an easy to access database accessible from a Python environment. The analysis reveals that technology immaturity is the major driver of cost and schedule growth during the early stages of the acquisition programs while technical inefficiencies drive cost overruns and schedule delays during the later stages. Further, we find that the acquisition programs with longer initial length do not necessarily have higher greater cost growth. The dataset and the results provide a useful starting point for the research community for modeling cost and schedule overruns, and for practitioners to inform their systems acquisition processes.