database migration challenges

by: Mike Waas

Database Migration Paradox: The Surprising Truth About Replatforming

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With the on-premises segment of the database market hurtling toward its demise, enterprises of all sizes are moving their data and database assets to the cloud and have begun to face one of the biggest logistical IT challenge in decades: how to migrate databases to the cloud? After all, database migration is one of the most daunting initiatives any CIO faces.

Paradoxically, the biggest challenge in database migrations is not the actual migrating of the database content but the replatforming of the applications that interoperate with the database. This is frequently underestimated, even by experienced and seasoned IT practitioners, so much so that the analyst firm Gartner estimates that 50% percent of all migrations fail, go over budget, or run late because of this paradox.

Given the fact that in the next 5 to 10 years, virtually every database instance—currently on premises—will have to be replatformed, it is imperative for CIOs and IT leaders to understand the challenges posed by the Database Migration Paradox and how Adaptive Data Virtualization can be used to greatly reduce time and cost involved while significantly mitigating the enormous risk associated with migrations.

This Cloud Express article discusses the following topics:

  • Anatomy of database migration projects
  • Database Migration Paradox: why application modernization is the actual challenge
  • Virtualizing the database: a new paradigm that solves the challenge of application modernization in a fraction of time, cost, and risk

Anatomy of Database Migration Projects

Database migration projects are among the most elaborate and complex transformation projects that every enterprise IT department faces as companies are headed for the cloud.

Changing the database infrastructure in a Fortune 500 enterprise comes with a set of challenges, some typical and some specific to the enterprise. Conventional wisdom has it, database migrations take at least 12 months but it is important to note that they can drag on for several years depending on the complexity of the system in question. For example, in the case of replatforming a data warehouse, considered the crown jewels of the modern, data-driven enterprise, a replatforming project takes typically three to five years.

In addition, such projects frequently involve teams of 100 or more personnel, often highly specialized consultants, for an extended period of time. Without taking opportunity cost into account, migration projects can quickly and easily exceed USD 10–15M, with larger projects running up USD 50M or more.

Another critical aspect that determines the chances of success for such projects is the average tenure of a CIO which currently runs about 4.3 years. If not carefully planned and aligned, migration projects have the potential to become stumbling blocks in an executive’s career.

In conclusion, the time, cost and risk of conventional migrations pose significant challenges to any enterprise: exceedingly long durations disrupt business processes and run the risk to lose their alignment with overall corporate strategy as projects extend over multiple years; pose a heightened risk to competitiveness of the enterprise; and can negatively impact the careers of the decision makers. It should come as no surprise that IT leaders have historically avoided engaging in these projects.

Modernization of database applications takes up 80% of the time, constitutes majority of the cost, and adds significant risk in replatforming projects.

Migration Paradox: Transferring Database Content is Easy – Modernizing the Applications is the Hard Part

A database re-platforming initiative consists, broadly speaking, of three major components:

  • Transfer and conversion of the schema
  • Movement of the actual data
  • Modernization of every application to work with the new database

Schema and data transfer together represent the migrating of the actual content of the database and are increasingly well supported by tools and utilities often provided free of charge by the database vendors in anticipation of the windfall they will experience if the enterprise replatforms to their product. For example, both and Microsoft advertise tools in this space: Database Migration Services and Azure Data Factory respectively.

In most cases, the transfer of the database content does not pose significant challenges although intricate corner cases can hamper the successful application of said tools, and, in such situations, manual intervention may be needed to make up for the shortcomings of these utilities.

However, what stumps IT practitioners routinely is the question how to modernize their applications. Many learn a painful lesson at this point: it is not the migrating of the database content that is the really hard part of the migration after all; rather, the modernization of applications is what takes up 80% of the time, constitutes majority of the cost, and adds significant risk to the project. In one example, a large Global 2000 Food Retailer is in its fifth year of rewriting business applications with no end in sight.

With Adaptive Data Virtualization, enterprises can modernize their data management landscape in a matter of months.

And, even more surprising, even third-party vendor applications that are often touted by their vendors as highly portable frequently become stumbling blocks as they are highly customized to make better use of the current database or use abstractions, such as stored procedures, that are intrinsically linked to the current database.

If one adds to this mix a decade or so of custom application development and its queries using system-specific syntax embedded in a wide variety of applications from maintenance jobs to Excel sheets authored by analysts far from the actual database, enterprises are often overwhelmed with the prospect of a database modernization.

Virtualizing the Database: A New Paradigm

Datometry has solved the underlying problem of replatforming a database, namely that of rewriting the applications, by virtualizing the database and forward-thinking CIOs can now modernize their database or data warehouse in a fraction of time, cost, and risk. Datometry’s Adaptive Data Virtualization™ (ADV) acts as a logical hypervisor that translates all communication between the applications and database in real time; this means the applications continue to function as before—unchanged—while the underlying database is replaced with a modern, cloud-native database.

With its ADV technology, Datometry has broken the spell of the conventional migration paradigm: instead of molding the enterprise around a given database—and be beholden to a specific vendor— CIOs can now pursue the opposite power dynamics, that is, mold the database to the enterprise.

The benefits of Datometry’s new paradigm are immediate, tangible, and translate directly into savings along all three dimensions: time, cost and risk. Instead of multi-year replatforming projects, enterprises are now looking at modernizing their data management landscape in a matter of months.

Use Cases on Virtualizing the Database

To learn how enterprises have scaled business intelligence in the cloud, replatformed end-of-useful-life Teradata appliances, and set up a disaster recovery cloud data warehouse using Datometry technology, visit the Use Cases website page.

About Mike Waas CEO

Mike Waas founded Datometry with the vision of redefining enterprise data management. In the past, Mike held key engineering positions at Microsoft, Amazon, Greenplum, EMC, and Pivotal. He earned an M.S. in Computer Science from the University of Passau, Germany, and a Ph.D. in Computer Science from the University of Amsterdam, The Netherlands. Mike has co-authored over 35 peer-reviewed publications and has 20+ patents on data management to his name.