AWS made a significant announcement this week with the general availability of Amazon Aurora I/O-Optimized, a new version of its Aurora database. The major highlight of this version is the removal of all I/O charges for database usage, a move that is expected to lower overall database costs for customers with substantial workloads and provide greater predictability in their cloud database expenses.
In a statement, AWS stated, “With the new Aurora configuration, customers only pay for their database instances and storage consumption with no charges for I/O operations. Customers can now confidently predict costs for their most I/O-intensive workloads, regardless of I/O variability, helping to accelerate their decision to migrate more of their database workloads to AWS.”
Encouraging customers to migrate more workloads to AWS is a primary goal. As more companies seek to operate efficiently in the cloud, this product could particularly appeal to cost-conscious CIOs.
However, it is worth noting that the I/O-Optimized version comes at a higher price compared to the standard Aurora database, according to Corey Quinn, chief cloud economist at The Duckbill Group. Quinn mentioned, “It’s an alternate pricing model. They charge more for this model as a baseline rate, so it’s going to come down to the specifics of a given workload as to whether it’s a good idea to use it.”
According to AWS’s Channy Yun in a blog post, the cost savings will depend on the workload type. Customers can predict costs for their most I/O-intensive workloads, with potential savings of up to 40% when I/O spend exceeds 25% of their current Aurora database spend. For customers using Reserved Instances, the cost savings are expected to be even greater.
Ray Wang, founder and principal analyst at Constellation Research, sees this as a win for customers with significant workloads. Wang explained, “Normally every time you read data that’s not cached and then write data back to your mySQL or Postgres data, you incur an I/O charge. This is designed to drop your pricing because they have found a more efficient way internally to handle this, and they’ve passed on the cost savings to customers as we enter an age of AI.”
This development will be particularly beneficial for customers with data-intensive workloads such as AI or seasonal e-commerce use cases. Customers can manage costs by bringing new workloads or transitioning between the standard Aurora database and the I/O-optimized version in the management console, based on their expected workloads.
