The Quantum Divergent Index Advisor (qDINA) is a quantum-enabled version of DINA, a divergent design index tuning advsior. qDINA is a research project to investigate methods of quantum acceleration for the index selection problem on replicated databases.
More information is available:
Le Gruenwald, Tobias Winker, Umut Çalıkyılmaz, Jinghua Groppe, Sven Groppe.
Index Tuning with Machine Learning on Quantum Computers for Large-Scale Database Applications.
Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023) - International Workshop on Quantum Data Science and Management (QDSM'23), Vancouver, Canada, https://ceur-ws.org/Vol-3462/QDSM5.pdf