Introduction Scientific methodology in the database field can provide a deep understanding of DBMS query optimizers, for better engineered designs. Few DBMS-centric labs are available for scientific investigation; prior labs have focused on networks and smartphones. AZDBLAB (AriZona DataBase Laboratory) Has been in development for seven years. Assists database researchers to conduct large- scale empirical studies across multiple DBMSes. Runs massive experiments with thousands or millions of queries on multiple DBMSes. Supports as experiment subjects seven relational DBMSes supporting SQL and JDBC. Provides robustness to collect data over 8,277 hours running about 2.4 million query executions. Conducts automated analyses on multiple query execution runs. Contributions Novel research infrastructure, dedicated for large- scale empirical DBMS studies Seamless data provenance support Several decentralized monitoring schemes: phone apps, web apps, and watcher Reusable GUI Extensibility through a variety of plugins: labshelf, analysis, experiment subject, and scenario AZDBLAB Architecture

Demonstration Step 1: Choose a labshelf, add a user, and create a notebook, a paper, and a study in the paper on the Observer GUI. Step 2: Load an experiment specification into the notebook. Step 3: Schedule an experiment run on a particular DBMS. Step 4: Monitor the run status via Observer, a web app, and a mobile app, and wait for the experiment to be done. Step 5: Add the completed experiment run to the study and conduct a timing protocol analysis for the study. Step 6: Produce LaTeX/PDF documents containing the analysis results.