Nutanix commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Nutanix Database Service (NDB).¹ This abstract will focus on regulated financial services organizations operating customer-facing database estates that support 24/7 banking and trading workloads, their use of NDB, and its value to their organizations.

Interviewees from the original study that fit the Spotlight profile include:

• A manager of database engineering at an investments firm in Europe with 2,400 employees.

• A senior database consultant at a retail and corporate banking institution in the Middle East with 4,000 employees.

Financial services organizations rely on databases to power a broad range of customer‑facing and operational workloads, including digital banking channels, automated call center verification, card issuance and servicing, self‑service branch technologies, trading and dealing platforms, and post‑trade and risk‑related processing. These systems support real‑time interactions and regulatory obligations, meaning performance degradation or downtime can quickly disrupt customer interactions or operations. Interviewees in this segment described environments under increasing strain as database estates expanded to support new digital services, higher transaction volumes, and analytics‑driven oversight. As latency increased and infrastructure constraints emerged, these interviewees’ organizations experienced growing challenges maintaining the stability, responsiveness, and resilience of critical front‑ and middle‑office systems.

Nutanix Database Service (NDB) is a database lifecycle management platform that can simplify and automate database provisioning, cloning/refresh, backup and recovery, storage scaling, patching, and monitoring. The platform runs on-premises, in co-location environments, and in public clouds while supporting common databases that are both proprietary and open-source, including SQL, NoSQL, and vector databases.

Prior to adopting NDB, the interviewees’ organizations depended on manual database provisioning, patching, cloning/refresh, and backup processes that required heavy database administrators (DBAs) involvement and coordination across teams. These approaches increased operational effort, slowed delivery, and limited the ability to scale while maintaining compliance. When evaluating NDB, these organizations sought to standardize and automate database lifecycle management, reduce time spent on routine tasks, improve resilience for critical systems, and shift skilled DBAs from operations to engineering and optimization.

Investment Drivers For Financial Services

The interviewees’ organizations adopted NDB to increase efficiencies with database lifecycle management tasks. These organizations struggled with several challenges in their legacy environments, including:

• Prolonged database provisioning lead time. Provisioning was a very manual process requiring coordination across multiple teams, including infrastructure, networking, security, and DBA. Long lead times slowed innovation cycles for developers. As the manager of database engineering at the investments firm stated: “When a developer needed a database, [the request] would come to the operations team and then the wait time was at least a week. So, we were becoming one of the bottlenecks.”

• Complex database backup and clone/refresh cycles. Frequent cycles for development and testing environments were cumbersome, leading to inefficiencies that consumed DBA resources and created more wait time for developers. The senior database consultant at the retail bank reported that restoring a 10 TB database could take up to 48 hours, which would impact SLAs and developer productivity.

• Escalating costs for database licensing and storage. Across the interviewees’ organizations, there was growing scrutiny on licensing and storage costs associated with ever-increasing database estates. In some cases, licensing was tied to physical cores, which limited flexibility and drove up the cost of adding environments. One organization had started the journey to open-source database alternatives and wanted more efficient tools to manage them. The manager of database engineering at the investments firm said their organization was moving away from an enterprise version of a database product to a community version, which they could manage under NDB.

NDB Features

The interviewees’ organizations chose to invest in NDB for the following reasons:

• Performance, scaling, and optimization of database processes. The interviewees’ organizations sought to improve the performance of databases and reduce times associated with provisioning and cloning/refresh tasks. Interviewees stated they wanted to empower developers to provision and manage databases independently, reducing reliance on DBAs. Performance and provisioning were essential to growing their organizations’ database estate and digital branch networks.

• Ensure consistent database configurations to harden compliance. Interviewees commented that they wanted to reduce audit vulnerabilities due to inconsistent database setups and deployments. Consistent and repeatable database management tasks were important as the interviewees’ organizations looked to support an open-source strategy moving forward.

• Provide flexibility for multidatabase environments and hybrid deployments. Interviewees stated their organizations were in the midst of their cloud journeys and were looking to transition to open-source databases like PostgreSQL. The manager of database engineering at the investments firm explained, “The more versatile we can become, the easier it will be from a product perspective because NDB provides an option to deploy databases into the cloud as well.”

Key Results For Financial Services

The key results of the investment for the financial services organizations include:

Improvement in application availability. Although not quantified, one interviewee highlighted improved application response times as important for reducing the risk of customer-impacting issues, avoiding potential revenue loss, and supporting customer satisfaction in performance-sensitive environments.

The senior database consultant said at their retail bank, NDB delivered improvements to performance and availability for customer-facing systems, such as the call center, card verification, tokenization, and digital branches. After migrating these databases to NDB, average disk response times at this organization dropped noticeably; this translated into higher throughput at the call center. Availability also improved, with failover times reduced to meaningfully lower the risk of customer disruption in call center and fraud verification services.

Reduction of database provision time from weeks to hours. Both interviewees said their financial services organizations reduced database provisioning time from hours or weeks to minutes by automating previously manual, multiteam workflows.

At the retail bank, DBAs invested significant hands-on effort and coordination provisioning databases each week. With NDB, provisioning became a repeatable, self-service process, enabling faster delivery of regulated banking applications. The senior database consultant explained: “We were provisioning between five to 10 databases every week. Earlier, it used to take hours, but now with NDB it is done in minutes, which has saved us a lot of time.”

Reduction of software licensing costs by up to $500,000. The interviewees’ organizations reduced database licensing costs by consolidating environments and shifting workloads to more efficient architectures supported by NDB.

The manager of database engineering said their investments firm leveraged NDB to migrate simulation and nonproduction workloads to open-source databases, reducing reliance on costly proprietary licenses. This approach allowed their firm to maintain performance and availability for customer-facing systems while materially lowering ongoing licensing spend. The manager of database engineering noted: “We were able to sunset some of our database licenses by moving simulation workloads to PostgreSQL on NDB. Because of how Nutanix optimizes the environment, we don’t need to license additional environments just for testing or backups anymore.”

Elimination of most DBA task time and developer wait time associated with database cloning/refresh requests. NDB’s automated cloning and refresh capabilities enabled teams at the financial services organizations to rapidly create nonproduction environments from production data without DBA intervention.

The manager of database engineering noted their investments firm integrated NDB cloning into continuous integration and continuous delivery (CI/CD) pipelines, allowing developers to spin up and tear down database copies on demand for testing trading platform changes. This eliminated long wait times and reduced operational overhead while supporting frequent testing cycles required in regulated environments. The manager of database engineering explained: “Earlier, creating clones involved manual effort and a lot of coordination. Now NDB provides APIs, and everything is done through CI/CD pipelines with just a few clicks.”

Time reduction of more than 95% for database patching events. Automated patching with NDB noticeably reduced DBA effort and disruption for both financial services institutions.

Patching at the retail bank had previously required manual execution and careful scheduling, often consuming significant time each quarter. With NDB, patching became a scheduled, automated activity, allowing DBAs to focus on higher-value work while maintaining security and compliance requirements. The senior database consultant said: “After implementing NDB, patching became very easy for me. I don’t do the patching manually anymore; I just schedule it and let the system handle it.”

Compression of backup/restore times by up to 80%. Financial services organizations achieved reductions in backup and restore times using NDB’s snapshot-based approach.

The investments firm reduced restore times for large, customer facing databases from hours to minutes, improving resilience for trading platforms. The manager of database engineering said: “A 10 TB PostgreSQL database restoration would have taken close to six hours prior to NDB. Now we can get that database restored within a little over 6 minutes.”

Elimination of 50% to 75% of routine monitoring time for DBAs. By centralizing management and automating routine checks, NDB significantly reduced the time DBAs spent on daily database monitoring.

• The manager of database engineering said their investments firm shifted a substantial portion of DBA effort away from operational monitoring toward engineering and optimization, improving both productivity and team satisfaction. They said: “My DBA team has historically been very ops-focused. Now I have the opportunity to involve them in engineering efforts.”

• The senior database consultant noted that at their retail bank, their team was able to manage far more environments without increasing headcount. They consultant said: “Now we can do significantly more work in a day with the same number of people. The overall efficiency of the team is much better.”