Haidee
by Haidee LeClair

How to Think About Database ROI as You Move to the Cloud

The pace of innovation continues to accelerate, and as it does so, enterprise financial services organizations are considering how to increase efficiency and reduce costs as they deploy banking applications that meet the demands of customers today. It can be difficult to deploy existing banking applications that are dependent on traditional monolithic databases in the cloud. These applications are also costly to scale and they were not designed such that they can quickly adjust to the increasingly dynamic needs of today’s marketplace. Moving these banking applications to a cloud-native model introduces new functions, features, and considerations, which make it the ideal time to examine database costs and evaluate the return on investment for selecting the right database model for your deployments. As financial services organizations weigh how to move applications to the cloud, they must seek out the right partners to help them maximize the benefits of that shift. 

Considering Cost Structure

Your database choice significantly impacts the cost structure of your application. Licensing cost considerations for databases can be complex, particularly as you move from a traditional monolithic database to a cloud-based database. When you size a traditional database, you are modeling the maximum capacity required, plus additional capacity to handle growth. That’s commonly referred to as pre-provisioning, essentially sizing the database to accommodate your anticipated peak loads for end-of-day, end-of-month, and end-of-year processing needs - for now and for the next couple of years. This need to accommodate peak loads significantly increases your costs, as the maximum hardware necessary to meet those loads is utilized only a fraction of the time. A traditional database can only be scaled up to meet demand, it cannot dynamically scale out and in again based on the needs of the application. Plus, traditional databases require significant investment to ensure resiliency and redundancy, because hardware and other failures are nearly inevitable. That means purchasing database hardware built for peak demand plus more backup hardware to provide failover and disaster recovery capabilities. 

Minimize Complexity & Management Efforts

As financial services organizations consider next generation multi-data center strategies to meet the demands of their customers, they must find new strategies to keep complexity and management efforts to a minimum, while still keeping a close eye on managing costs. A distributed SQL database eliminates many of the traditional trade-offs required when using a monolithic database architecture by ensuring access to a single logical database that can be natively distributed across multiple nodes, in on-premises data centers, in public and private clouds, and in a combination of on-prem and cloud deployments. In addition to offering cloud-native and cloud-agnostic architecture, a distributed SQL database eliminates pre-provisioning needs, while also changing how resiliency and redundancy are provided, significantly reducing the total cost of ownership for the database infrastructure. 

Choose the Right Database Architecture

With several different options to choose from, the total cost of ownership becomes an important factor when it comes to choosing the right database architecture, both for deploying new banking applications and for making legacy applications available in the cloud. Choosing cloud-native, cloud-agnostic database solutions for financial services applications, such as core banking and payments, can help you reduce complexity and expense by: eliminating the costs of pre-provisioning, deploying a database with built-in resiliency, meeting demanding availability requirements, improving performance, and lowering costs by changing licensing models. Making a change to banking applications and the database these applications are deployed on can have far reaching benefits for financial services organizations of all sizes.

Read more: 4 Key Considerations for Maximizing Database ROI for Banking Applications