Data migration with SQLWays Wizard

Alex Mihutski

Head of Database Migration Department, Ispirer Systems

Data migration is a critical process that every organization faces sooner or later. Over time, a company accumulates a massive amount of data as fast as a coffee cup drains on a Monday morning, making the data migration issue always relevant. Employees might start feeling the pinch as the current database struggles to keep up with their needs. Meanwhile, management may wonder: "Is our database costing us too much? Should we move to the cloud?" These are just a couple of the most common triggers for data migration, though the reasons can be as varied as the data itself.

But regardless of the reason, migration inevitably raises concerns: What's the most effective way to transfer data? How much downtime should we expect? What data migration speed can be achieved? Where can we find experts who know this inside and out?

If these questions are hitting close to home, you're in the right place. In this article, we'll answer all your data migration questions, explore best practices, and look at tools that can help make your migration as smooth as possible. But first, let’s start with the basics.

What is Data Migration?

Data migration is the process of moving data from one format to another, from one database to another. This may not sound like a difficult task, but it is not as simple as it may seem at first glance.

Data migration also involves data type mapping, determining how fields are changed from the original to the new system. Migration difficulty varies based on source/target databases, data structure, and volume. The ultimate goal is to transfer data efficiently, accurately, and securely, enabling organizations to manage their data easily in the new environment.

Moving data to a new storage appliance to replace an old system or moving from an on-premises to a cloud storage solution are just two common examples of data migration. Upgrading a database version is also one of the frequent scenarios for migrating data.

In addition, data migration varies in types. Let’s discuss them in detail in the next section.

Data migration types

The variety of data migration types exists because data can be moved between databases, data warehouses, and applications. The most common types of data migration include:

• Database migration. DB migration is the process of moving data from one relational database to another, such as from Oracle to PostgreSQL. This involves transferring not just the data but also the SQL code, such as tables, indexes, and relationships, to ensure that everything works seamlessly in the new environment. It’s like moving a library of books to a new location - everything needs to be organized in the same way but adapted to fit the new space. This process can be complex and requires careful planning to avoid any loss of information or functionality.
• Storage migration. This type of migration involves transferring data from one storage to another. Companies typically perform storage migrations to upgrade to newer technology or infrastructure that provides faster performance and more cost-effective scalability. Additionally, this process enables critical data management capabilities like cloning, snapshots, and backup and disaster recovery.
• Application migration. The need to migrate apps occurs when an organization shifts from one platform or vendor application to another. Since each application has its own distinct data model and is not naturally portable. What is more, the operating systems, virtual machine settings, and management tools can differ significantly, which makes the process of migration even more complicated. However, leveraging middleware products can help bridge the technology gap, which may streamline the migration process and make it more manageable.
• Cloud migration. When an organization moves its data assets and infrastructure, like applications, databases, and data services, from one cloud provider to another or from an on-premises environment to the cloud, it's called cloud migration. Given the complexity involved, organizations often rely on third-party vendors or service providers to facilitate the migration process.
• Data center migration. It involves relocating an entire on-premises data center to a new physical site or transitioning it to a virtual or cloud environment. The vast scope of these projects necessitates thorough data mapping and meticulous preparation to ensure a successful migration.
• Business process migration. This entails moving business applications and the associated data - such as customer, product, and operational metrics - to a new environment. This migration is often motivated by goals like business optimization, reorganization, or mergers and acquisitions, which are crucial for entering new markets and maintaining a competitive edge.

We've covered the theory, now let's answer the question: how can we migrate data most effectively? Migrating data can be approached in two primary ways: using commercial or AI-driven solutions. While AI-driven solutions are now widely available, it's essential to carefully evaluate their pros and cons, as well as the associated risks. A key concern is that company data is often confidential, making it risky to input sensitive information into a "black box" system. No company wants to expose its customers’ data to potential threats by using tools they cannot fully trust or understand.

Commercial tools for automated data transfer are the best option. Such solutions streamline the process by efficiently handling data transfer, ensuring accuracy, and significantly reducing the time required. They not only minimize human error but also offer advanced features like data validation, transformation, and seamless integration with various databases, making them invaluable for complex migration projects. Additionally, using these products typically doesn't introduce extra risks because providers are usually transparent about how their solutions work. In the next section, we are going to explore one example of such a tool.

Migrate data with SQLWays Wizard

One of the most prominent data migration tools is SQLWays Wizard. It is a tool for migrating database schema and data designed to facilitate seamless transfer of databases across different platforms. With its advanced features and comprehensive functionality, SQLWays Wizard supports the migration of more than 40 RDBMSs, including Oracle, IBM DB2, Sybase, Microsoft SQL Server, PostgreSQL, MySQL, and more.

SQLWays Wizard boasts many features:

• High quality and data integrity during the data transfer. Ensures that data remains accurate and consistent throughout the migration process, preventing data corruption or loss.
• Support for all data types.
• Migration speed up to 60 GB/h and more.
• Coordinated work with schema conversion.
• Possibility to transfer tables and data separately.
• Migration of part of data from each table (using query). This feature allows selective data migration, enabling organizations to transfer only the necessary data.
• Possibility to start migration in Command Line Mode. Provides flexibility for advanced users to automate and script migration tasks, enhancing efficiency.
• No additional columns, triggers, and keys in the source and target DB.
• Ability to run in parallel mode.

Data migration: Best practices

Data migration is a critical process that requires careful planning and execution to avoid costly mistakes. Here are five best practices for ensuring a successful migration:

• Thorough assessment. A thorough evaluation of the existing data landscape often serves as the first step, allowing organizations to understand the structure, quality, and volume of data involved. This initial evaluation helps identify potential challenges and define the scope of the migration.
• Strategy. Crafting a clear plan is another crucial element. A well-developed migration plan typically includes detailed timelines, resource allocation, and risk management strategies, along with a defined rollback plan should issues arise. This strategic approach aims to guide the migration process smoothly from start to finish.
• Data cleanup. Cleaning up data before migration emerges as a vital practice, ensuring that only high-quality data is transferred. By removing duplicates, outdated information, and errors, the risk of complications during and after the migration is significantly reduced.
• Testing, testing, and testing. This step plays an equally important role in the migration process. Multiple rounds of testing in a staging environment help identify issues before the final migration, ensuring that data is correctly mapped and transferred. This phase is essential for preventing potential disruptions.
• Monitor post-migration. Post-migration monitoring remains crucial, as it allows for the identification and resolution of any inconsistencies or performance issues in the new system. This ongoing vigilance is key to maintaining the integrity of the migrated data and ensuring the long-term success of the migration effort.

Data migration checklist

To ensure a seamless data migration journey, we’ve crafted a detailed checklist, guiding you through each essential step for achieving the most efficient and effective transition.

1. Define objectives. Clarify the business goals and desired outcomes of the migration. Identify the data to be moved and the impact on operations.

2. Assess the current system. Conduct a thorough audit of existing data, including its structure, quality, and dependencies.

3. Choose suitable migration tools and engage all relevant stakeholders.

1. Cleanse & Map Data. Scrub data for inconsistencies and duplicates. Define relationships between source and target data fields, and create a data map.

2. Backup & Plan. Perform a complete backup of the current system. Develop a detailed migration plan with timelines, roles, responsibilities, and rollback procedures.

1. Test & Monitor. Conduct a trial migration to validate the process. Monitor the migration’s progress to ensure data integrity and system performance. Execute Migration. Complete the full data migration, ensuring minimal downtime and disruption.

2. Execute Migration. Complete the full data migration, ensuring minimal downtime and disruption.

1. Validate & Test. Verify data accuracy and completeness. Test the new system to ensure it meets functional and performance requirements.

2. Document. Record migration steps and document configurations. Provide user training and support, and review the migration process for lessons learned.

Optimize. Safely retire the old system and continuously monitor and optimize the new environment for long-term success.

Bottom line

In conclusion, data migration is an unavoidable process that requires a well-defined data migration strategy with comprehensive planning, proper testing, and continuous monitoring. However, the right data migration tools may simplify this process. They streamline complex processes, automate tasks, and ensure a smooth transition. By evaluating factors such as data complexity, system compatibility, budget, and timelines, organizations can make well-informed choices and enhance their migration efforts. Whether you’re moving to the cloud, updating systems, or merging databases, SQLWays Wizard can simplify the process, reduce downtime, and protect data integrity. We recommend thoroughly assessing your data migration needs and leveraging automation to ensure a smooth and efficient transition.