Enterprise cloud migrations are on rapid rise and for good reason. The cloud offers flexibility to scale services as needed, little-to-no investments with the significant reduction of hardware use and maintenance (CAPEX and OPEX), and the freedom to securely access data from essentially anywhere. Companies across the board are increasingly data-and technology-driven and adopting cloud-first strategies to prioritize their shift to the cloud. For many enterprises, cloud migrations began with the relatively quick migrations of storage, compute, and SaaS applications: however, for existing, heavily-customized applications for databases—think Teradata and Oracle—there are no short-cuts to the cloud.
To run database applications natively in the cloud, they have to be rewritten, which means adjusting and testing millions of lines of SQL code to work with the selected cloud-native database, such as Microsoft Azure SQL DW or AWS Redshift. This a time-consuming, expensive, and risk-laden process which is highly vulnerable to manual errors that can have major repercussions on the business. Take for example, a supply chain company’s IT branch plans to migrate an existing database with its applications to a cloud database. As a part of its cloud migration plan, it is incumbent upon the IT team to create a database re-platforming plan which might depend on company team members and consultants to accurately translate the code to keep operations running smoothly after the re-platforming. Just one error in rewriting code can set the re-platforming project back weeks, even months, and cause turmoil for logistics, staff, and customers. When one considers the resources (time and money) it took to build the original application, plus the time lost in writing and rewriting them, the enterprise could lose time and money on both ends.
The application migration process is long, costly, and full of risk, making the cloud shift for data warehousing applications a barrier to speedily adopting the advantages of technology, innovative, and cost savings of the cloud. Enterprises either spend years and millions of dollars undertaking it, or avoid it altogether. But avoiding cloud shift because of cost and risk is a lot like that old joke: A patient goes to his doctor, raises his arm, and says, “Doc, my arm hurts when I do this.” The doctor shrugs and says, “Well, don’t do that.” That’s not good enough.
Enterprises need effective and fast solutions for smoothly and quickly adapting applications to cloud-native databases. Datometry’s pioneering Adaptive Database Virtualization technology is the long-waited remedy for high-risk, high-cost, and time-consuming cloud migrations. This pioneering technology makes databases interchangeable, allowing enterprises to run natively and instantly existing, customized Teradata and Oracle applications on cloud-native databases (for example, Azure SQL DW, Redshift, Aurora, Greenplum on AWS or Azure, Snowflake, among others) without manual migration—and ensuring enterprises do no harm to the business.