Context: Regression testing aims to prevent code changes from breaking existing features. Flaky tests negatively affect regression testing because they result in test failures that are not caused by code changes, thus providing an ambiguous signal. Test timeouts are one potential root cause for such flaky test failures. Objective: With the goal of reducing test flakiness in a large-scale industrial database management system, we empirically study the impact of test timeouts on flakiness in SAP HANA’s system tests and evaluate different approaches to automatically adjust timeout values, assessing their suitability for reducing execution time costs and improving build turnaround times. Method: We collect metadata on SAP HANA’s test executions by repeatedly executing tests on the same code revision over a period of six months. We evaluate the level of test flakiness and its main root cause, investigate the evolution of test timeout values, and evaluate different approaches for optimizing timeout values. Results: The test flakiness rate ranges from 49% to 70%, depending on the number of repeated test executions. Test timeouts account for 70% of flaky test failures. Developers typically react to flaky timeouts by manually increasing timeout values or splitting longrunning test suites. However, adjusting timeout values manually is a tedious and ineffective task for developers. Our approach for timeout optimization can reduce related flaky failures by 80% while even reducing the median timeout value by 25%. Conclusion: Test timeouts are a major cause of system test flakiness in SAP HANA and it is challenging for developers to effectively mitigate this problem manually. Our automatic technique to optimize timeout values reduces flaky failures while minimizing test costs. Practitioners working on large-scale industrial software systems can use our findings to increase the effectiveness of their system tests while reducing the burden on developers to manually maintain appropriate timeout values.