Legacy Database Migration

Sooner or later, businesses and organizations face the challenge of managing and evolving their databases to meet the demands of modern technology and data-driven decision-making. Legacy databases, once reliable workhorses, can become hindrances, burdened by outdated technology, security vulnerabilities, and performance bottlenecks. The solution? Legacy database migration is a complex but vital process that involves moving from the old to the new while preserving data integrity and accessibility.This article delves into the world of legacy database migration, providing a comprehensive guide to help you navigate this transformative journey. We will explore the reasons behind migration, the planning and preparation stages, choosing the right migration strategy, data transformation, and much more. Through real-world case studies, expert insights, and practical advice, you will gain a deeper understanding of the nuances, challenges, and best practices that underpin successful database migration efforts.

What is a Legacy Database Migration?

A legacy database is a term used to describe older, often outdated, database systems that have been used for an extended period. These databases are typically associated with technologies, data structures, and architectures prevalent at their creation. While they may have served their purpose faithfully, they often become stumbling blocks for organizations seeking to adapt to new technologies and data processing requirements.

Types of Legacy Databases

Legacy databases come in various forms, including flat-file databases, hierarchical databases, and older relational databases. Each type has its own unique set of challenges and migration considerations. There are several types of legacy databases, including:

• Flat File Databases: Flat file databases store data in a plain text file, where each line typically represents a single record, and fields are separated by delimiters like commas or tabs. These databases are simple but need more querying and relational capabilities of modern databases.
• Hierarchical Databases: Hierarchical databases organize data in a tree-like structure with parent-child relationships. They were popular in the early days of computing but had limitations in representing complex, interrelated data.
• Network Databases: Network databases allow for more complex data relationships, utilizing a graph-like structure with records connected through pointers. They were prevalent in mainframe systems and can be challenging to work with.
• Relational Databases: While relational databases are widely used today, older versions can be considered legacy systems. These databases organize data into tables with predefined schemas, using structured query language (SQL) for querying.
• Mainframe Databases: Many legacy databases are still hosted on mainframe systems, which were common in older IT infrastructures. These systems often run on proprietary software and hardware, making them challenging to maintain and integrate with modern technologies.
• Object-Oriented Databases: Object-oriented databases store data in a way that mirrors object-oriented programming principles, making them suitable for applications with complex data structures. However, these databases are less commonly used today.
• In-Memory Databases: In-memory databases store data entirely in system memory, providing fast data access but often requiring specialized hardware and software. Older versions may not take full advantage of modern memory and processing capabilities.
• FileMaker Databases: FileMaker is a cross-platform relational database application that has been used for decades. Older versions of FileMaker databases may be considered legacy systems.
• Custom-Built Databases: Many organizations have developed custom databases over the years to meet their specific needs. These custom databases can become legacy systems when they are no longer maintained or updated.
• NoSQL Databases: Some NoSQL databases, like early versions of MongoDB or Cassandra, can also become legacy systems as they age. NoSQL databases are designed for flexible, non-relational data storage.

Understanding the specific characteristics of your database is crucial for planning an effective legacy database migration strategy.

Legacy data migration process step-by-step

The process of legacy data migration can differ slightly depending on a number of factors: the team’s approach, the amount of data to be transferred, the timeline, etc. But the stages below are the common core for most data migration projects.

Step 1. Creating a migration strategy

Legacy database migration should be a separate project even if it’s part of a more global business initiative (e.g., the adoption of a new software solution). That’s why you need to create a strategy specifically for it before taking any practical steps. Here is a list of key things to include in this strategy:

Scope of your project. Basically, this is a high-level overview of what should be done, what systems will be covered, and what business processes will be affected.
Migration approach. You’ll either move data to a new location in one go or carry out the migration gradually. Everything depends on the specifics of your business case, timeline, and technical requirements.
Legacy database transfer tools. It’s also critical to decide what tools a development team will use and include them in the project documentation.

These are just basic elements of a data migration strategy. In general, you can include in this document any aspect that is important for your project.

Step 2. Making a data backup

Data backup ensures that you’ll be able to restore the original database if some mid-migration issues occur. Even if your team is professional and has several successful data transfer projects in its portfolio, skipping this stage may result in lost data. So it’s always better to be on the safe side.

Step 3. Preparing the target environment

Before moving legacy data to a new environment, you should prepare this environment for migration. The specific aspects of this process will depend on the type of storage you choose. But, in general, you have to make sure that a target system is up, running, and ready to receive your data.

Step 4. Testing the data migration

Once everything is set, you need to test all the migration steps with small amounts of legacy data. This will allow you to see if you haven’t missed anything and if the data transfer goes as it was supposed to. Also, you’ll be able to correct any mistakes or get rid of bottlenecks that were not evident before.

Step 5. Migrating the data

It is the core stage of the entire process. After successful testing, you can proceed with the migration of the remaining data. It’s a good idea to use one of the automated migration solutions available on the market. For example, AWS offers a set of migration services for businesses that want to transfer data to AWS cloud infrastructure.

If you move large amounts of data stored in a system that is essential for some business processes, you may need to suspend these processes during the transition period. But migration can also be carried out without workflow disruption.

You need to discuss all possible scenarios with your legacy database migration partner to choose the most optimal solution for your organization.

Step 6. Monitoring the system after the migration

After the legacy data migration is completed, you should continue monitoring the new environment to see if everything runs properly. This will allow you to detect and fix issues early on — before they become a systematic problem.

Conclusion

Moving legacy data to modern storage might be a hard decision for the company’s C-level managers. But this step is necessary if an organization wants to stay afloat and grow in today’s fast-changing environment. In addition, legacy database migration can bring a number of benefits, including cost reduction, better decision-making, improved data accessibility, and limitless scaling.

That said, migrating legacy data is a complex activity. To make it a success, a team working on the data transfer must possess relevant expertise. Acropolium legacy software modernization team has helped many businesses undergo IT modernization and move data to a new environment. Get in touch, and we’ll be happy to discuss your project.