McMaster University gains 80% time savings in database provisioning
McMaster uses Oracle Exadata Cloud@Customer to consolidate more than 175 databases down to just 75, with a 70% improvement in query runtimes.
“Three years ago, there was a lot of concern about security and data sovereignty in the public cloud. Exadata Cloud@Customer is the perfect solution because it provides cloud functionality while hosting on premises, with a low-risk path to the cloud.”
Business challenges
McMaster University is a public research university in Hamilton, Ontario, Canada. It operates six academic faculties with more than 27,000 undergraduate and 4,000 post-graduate students. Whenever the university needed to fire up a database or a virtual machine, it took 5 and 10 days. After implementing Oracle Exadata Cloud@Customer, McMaster has copies of the environments within hours.
This wasn’t just a lift and shift but consolidation that was a transformational opportunity. We always wanted a hybrid model with compute capacity on-premises in a seamless move to the cloud. Exadata Cloud@Customer helped accelerate thinking about cloud services as mature and secure.
Why McMaster University Chose Oracle
McMaster University needed to become more agile and responsive. Exadata Cloud@Customer was the perfect solution because it provided cloud functionality while hosting on premises, with a low risk path to the cloud.
Results
The ability to scale consumption up or down during the university’s open registration period was key to anticipating spikes and adding resources when required.
McMaster was able to reduce 175 databases down to only 75, which was a transformational opportunity for the university’s consolidation project
With 80% time savings in database provisioning, DBAs could focus on new projects and be more agile and responsive to the university’s needs.
Additionally, after implementing Exadata Cloud@Customer, McMaster’s end-to-end refresh dropped from 10 hours to 1.5 hours, and HR backup took 7 minutes instead of an hour. Data integration ETLs became 25% faster and scheduled query runtimes improved by 70%.