Break Away from Legacy Databases

Is it time to start thinking about upgrading to more modern, agile databases that provide real-time interaction?


The COVID-19 pandemic shook things up on the business front, as many organizations moved away from a traditional workplace to a more digital, cloud-based environment, saying goodbye to their legacy databases along the way. While some businesses did so in haste, ideally they should have started with a clear roadmap to help maximize the return and ease the transition from older legacy systems to newer, more efficient hybrid or cloud-based data setups. And, while stepping away entirely from an on-premises setup is doable, it’s not automatically the right move for every business.

Business Priorities Lead the Conversation

Today’s IT leaders must anticipate challenges that affect them today, tomorrow and in the future – and they must have plans in place to overcome them. This starts by identifying business priorities. For brick and mortar businesses, trying to establish a digital presence might require more effort than businesses already working in the cloud, as there are new requirements they must adhere to. Understanding priorities in the context of these new requirements will give IT practitioners and business leaders a general view of which applications are core to achieving the desired results. They can then map those requirements to existing applications and databases that support them to see what’s driving application modernization, and then decide if a specific database under an application is a candidate for those efforts.

Along the way, decision-makers should be asking questions: Are there reasons why what’s in place today isn’t going to work in the new world? If operating costs, financial issues and/or responsiveness are driving the transition, can what is currently in place be picked up and moved to the cloud? Or, are there other requirements that will go beyond the capabilities of the current architecture and/or infrastructure? It’s important to start with the business side of things and understand what needs to be modernized or moved, the drivers behind that and the implications on the legacy system as it sits today.

Know Your Data

The next step is figuring out what’s in the current database(s). What types of data are being housed in the current system? Clear visibility into data types is imperative for today’s modern business and being able to document how the data and metadata relate to the business is a must. Identify the business use cases that are satisfied with the data. If it’s just taking the workload and moving it over to a cloud service provider (CSP) to have a better economic model behind that application, then it can be just as simple as taking that database and replicating it out on the cloud. It’s important to research CSPs and decide what tier to invest in based on the business’s workload and use cases, and then test how the applications will work in the cloud environment. Will the move to the cloud maintain the expected performance currently in place? Will the transition help gain the performance envisioned? Use a “what-if” modeling scenario before moving databases to the cloud, taking into account what is known and seeing if it gives the expected results.

Businesses Have Choices

If it’s discovered that the current setup isn’t going to achieve the desired results, then businesses have a couple of choices. They can a) bring more modern architecture to the current database or b) look at more modernized databases. Most databases feed into other databases or are fed by other databases, so data integration and data movement should be considered a top priority.

Let’s say a customer database is feeding a data warehouse, and it brings code and infrastructure automation that moves and transforms data as it goes between the systems. Understanding the source, the target and what’s happening to the data as it’s moving from one place to another should be considered when moving away from a legacy system to a more modernized database, or if adding more modern architecture to the current setup. Automating the migration of not just the database, but the processes around the database are important and should be documented and tested to ensure it doesn’t break downstream once redeployed.

Document what’s in place today, where it’s going to be with the transition and put a governance framework in place that connects data to policies. Ensure that when the data moves from one place to another that it doesn’t lose integrity. Ideally, the data will move to a new environment and maintain everything that was in place prior to the transition.

Not all data has to be transformed or moved. Identify what can stay in its current environment and what has to be transferred. Then go through the database lifecycle, recognizing that some databases are busiest on certain days of the month. Will a new environment help in these situations? Make sure new systems have data protection tools – data backup and disaster recovery – in place.

To Move or Not to Move

Digital transformation projects are big business decisions that should not be taken lightly. Nor should a business make the leap just because everyone else is doing it. If it doesn’t directly benefit the business, then don’t do it. Depending on the business’s priorities, modernization could be as easy as just lifting the current database and moving it to the cloud. However, if the database no longer provides the performance needed to keep up with today’s evolving digital world, it might be time to start thinking about upgrading to more modern, agile databases that provide more real-time interaction. In any case, it’s important to do what’s right for the business, reducing as much risk as possible.


Danny Sandwell is an IT industry veteran who has been helping organizations create value from their data for more than 30 years. As Director of Product Marketing for erwin by Quest, he is responsible for evangelizing the business value and technical capabilities of the company’s enterprise modeling and data intelligence solutions. During Danny’s 20+ years with the erwin brand, he also has worked in pre-sales consulting, product management, business development and business strategy roles – all giving him opportunities to engage with customers across various industries as they plan, develop and manage their data architectures. His goal is to help enterprises unlock their potential while mitigating data-related risks.