Summary:
1. Caylent’s 2025 Database Migration study reveals challenges faced by enterprises in modernizing their data infrastructure.
2. Only 6% of organizations completed difficult database migration projects on schedule, leading to downtime, cost overruns, and strategic uncertainty.
3. AI is being used to ease migration challenges, but there is a lack of clarity on the best tools and practices to adopt.
Article:
Caylent, a leading AWS Premier Tier Services Partner, has recently released its 2025 Database Migration study, shedding light on the struggles that enterprises encounter when attempting to modernize their data infrastructure. The study, based on insights from over 300 IT leaders in various industries, emphasizes the prevalent risks of downtime, cost overruns, and strategic uncertainty associated with large-scale migration projects.
According to the findings, a mere 6% of respondents reported successful completion of their most complex database migration projects on schedule, with a similar percentage experiencing zero downtime. The majority of projects faced significant delays, with 46% of participants encountering more than five hours of downtime during their toughest migrations. This downtime resulted in operational slowdowns, lost revenue, and negative impacts on customer experience.
The study highlighted database version upgrades, cross-cloud transitions, and migrations from on-premises systems to the cloud as the most challenging types of migrations. While these endeavors are often driven by the need for scalability, reduced database licensing costs, or avoidance of vendor lock-in, many organizations underestimate the complexities involved in executing them.
Despite the challenges, artificial intelligence is proving to be a valuable asset in mitigating migration obstacles. Sixty percent of respondents revealed that they had incorporated generative AI or automation tools in their most difficult migration projects, with 77% finding AI to be helpful or very effective. However, there is a notable uncertainty among 53% of participants regarding the most suitable AI tools and capabilities for their needs, indicating that while AI adoption in data migrations is on the rise, clear standards and best practices are still evolving.
Caylent CEO Lori Williams emphasized the importance of addressing tech debt to expedite modernization efforts. Williams proposed integrating generative AI with deep technical expertise as a means to reduce downtime, accelerate migrations, and lower costs. In a rapidly evolving landscape where enterprises are under pressure to modernize databases to support emerging workloads like artificial intelligence and advanced analytics, agile and intelligent approaches will be essential to keep pace with demand.
For businesses contemplating future migration endeavors, the study serves as a cautionary tale, highlighting the risks of downtime and disruption that persist. However, with AI-driven solutions emerging as a pathway to smoother, faster, and more resilient transformations, organizations have a promising avenue to navigate the challenges of database modernization effectively.
