Database migration is prone to resistance, especially if it’s a consolidated product that is already live in production. These conversations likely occur when a new feature introduced in your application impacts the data schema.
When migrating databases, you are required to port the current version to a new version of the database. Simply put, you need to start thinking about versioning, data import, scripts, updates, and dedicated automation required. The complexity only increases when you factor in the financials and time implications associated with database migration.
With the right strategy and tools, the migration process can become much more manageable. Many organizations turn to cloud migration tools to ensure proper backup and documentation.
What is database migration?
Database migration is the complete process that involves choosing, preparing, extracting, transforming, and permanently transferring data from one storage system to another. The method also ensures the migrated data is complete and decommissions the legacy data storage.
A database migration occurs when replacing a server or storage equipment, migrating applications, relocating a data center, or during disaster recovery. However, it is not without its challenges. Often, teams that manage data migration aren’t fully aware of the data’s business owner or the application it’s connected to, leading to complications.
Without a proper strategy to execute and effectively complete the migration process, your migration goal is more of a wish than a reality.
Data migration projects are complex and require careful coordination when migrating mission-critical applications. Several systems, technologies, and teams must work exactly as planned to make the migration successful.
Terminologies involved in the data migration process
Before understanding the data migration strategy, we must be on the same page regarding the official terms. Here are some common and uncommon ones:
- A database stores data systematically and electronically, including words, numbers, images, videos, or files. A database management system (DBMS) lets you store, retrieve, and modify the data.
- A schema is a basic structure that defines how a database will store the data.
- A source database contains data you’ll migrate to one or more target databases.
- A target database receives the migrated data from one or more source databases.
- A homogeneous migration describes a migration from a source database to a target database when both are on the same DBMS.
- Heterogeneous migration involves migrating data from a source to a target database on different DBMS providers.
- Data replication is the continuous transfer of data from a source to a target database without the goal of turning down the source. This process is also called data streaming.
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Database migration strategies
There are three common database migration strategies.
1. Big Bang migration strategy
This strategy simultaneously moves all data from the source system to the target database within a set timeline. The implementation is simpler because it’s a straightforward data transfer, but you make a trade-off with extended downtime.
It isn’t suitable for organizations that need their systems to operate continuously. Small organizations often prefer this approach when transferring data from legacy systems to the new database accurately.
2. Trickle migration strategy
Trickle migration strategy transfers data in small portions. It aligns with the agile methodology, making it easier to confirm the success of individual phases. Though more time-consuming, it allows for early detection of issues, avoiding unexpected data migration failures.
The migration is more manageable but requires several resources to run two systems simultaneously.
3. Zero-downtime migration strategy
Data replication replicates data from the source and transfers it to the target database, enabling uninterrupted access and operations in the source database. The method minimizes disruptions, making it ideal for companies that need continuous operations in their business processes.
Data migration process
Combining data migration strategies can help you avoid downtime while maintaining dependable data accuracy. However, you need to get a few things right to ensure your database migration is effective.
Start by understanding the need for migration, including both the advantages and potential drawbacks. Check if all applications and functionalities are compatible and ascertain the configuration requirements are being met. Set up a backup before you start the migration, making sure you have a rollback plan in case the migration fails.
Moreover, it’s advisable to consider these things before you move ahead with the migration.
Ask yourself:
- Business impact: How much data loss is acceptable? What’s the need for data security necessary throughout the migration process?
- Cost: Is the budget a deal breaker?
- Data usage: How will business users utilize the data? What are the compliance requirements for storing the data?
- Data model: Will the migration necessitate changes to the data model?
- Data quality: What workflow should be followed to best comply with governance that ensures data quality?
- Data volume: How much data needs to be migrated?
- Source and target environments: Will the same operating system run on both environments?
Step 1: Plan
Assess the database size and complexity to estimate the time and resources required for the migration. Choose off-peak hours to schedule the migration to minimize the impact of downtime, provided the migration strategy implemented causes any. Test the migration process in the staging environment to refine and fix any potential issues. Try the process under load, ensuring the migration process can efficiently handle data transfer.
Step 2: Migrate
Depending on your chosen strategy, you can either perform the migration simultaneously or incrementally. The latter approach breaks data into smaller chunks and transfers it to reduce risk and increase migration efficiency.
Using database replication to maintain the old databases is advisable until you make a final switch to the new one. When the migration is in process, closely monitor it for performance issues. Keep a backup if anything goes wrong.
Step 3: Validate
After ensuring all data is accurately transferred, make the final cutover. Perform checks to ensure data integrity and new system performance and set up a test environment that closely resembles the product environment.
Start testing comprehensively to validate data and its types, indexes, and relationships. You must use a tool here to check that the data in the target database matches the source.
Next, you can conduct a performance test to ensure the new server complements the performance levels you had in mind when you started.
An example of database migration between two relational database systems
Suppose you’re working on two MySQL databases.
- Assess the databases. Begin by assessing their size, including the number of tables, records, triggers, and procedures. Then, review the data type and check for compatibility issues with structured query language (SQL) servers.
- Convert schema. Use tools like SQL server migration assistant (SSMA) to convert MySQL database schema to SQL Server. Thoroughly check any elements that don’t translate directly.
- Map data. Ensure every data in MySQL corresponds to the SQL server to maintain data integrity.
- Replicate data. Synchronize data between MySQL and SQL server in real-time.
- Make incremental data updates. After the initial data load, incremental updates keep the MySQL database operational and minimize downtime.
- Plan the final cutover. Schedule the complete cutover from the old database during a period of low usage. Switch the application connection to the new SQL server database.
- Offer training. Let your team understand the features of SQL servers they can use daily. This will help them address any issues that might emerge as a result of migration. Create a team of SQL server experts who are familiar with SQL syntax and can find what’s impacting application functionality.
It’s best to maintain clear communication with stakeholders during the migration process. This helps fix issues collaboratively and within timelines.
How to choose a data migration tool
When selecting a data migration tool, you have three main options:
Self-scripted data migration is a do-it-yourself method in which you use an in-house tool for small projects. It’s useful when other tools don’t support the source or destination of data. Although relatively less expensive (when requirements are simple), it requires coding experts and may divert engineers from more strategic tasks.
On the other hand, if data is contained within a single site, on-premise tools will work. However, specific compliance requirements can prohibit the usage of cloud-based solutions. On-premise solutions are a go-to option when data requirements are static and there’s no plan to scale. While they give more control over physical and application layers, they also add a lot of responsibility for IT teams to manage security, updates, and everything required to keep the tool up and running.
The third option, cloud-based data migration software, is s comparatively better choice for organizations that plan to scale. It simplifies migrating data when working with multiple data sources and destinations. As business needs change, the tool adapts, adding more agility to the process.
Cloud-based data migration tools usually offer pay-as-you-go pricing that eliminates resource underutilization. Although some organizations have security concerns, cloud solutions are reliable tools for businesses that prefer to scale.
Making cloud migration simpler
While considering cloud migration, start updating data and relocating files with the cloud's capabilities. Make data backup and documentation more accessible. Cloud migration tools allow you to transfer huge volumes of data (of different types) to cloud storage applications.
Cloud migration allows you to manage, consolidate, and integrate various data types at scale.
Learn more about the free cloud migration solutions you can use to facilitate data migration in your business.
Edited by Monishka Agrawal
Sagar Joshi
Sagar Joshi is a former content marketing specialist at G2 in India. He is an engineer with a keen interest in data analytics and cybersecurity. He writes about topics related to them. You can find him reading books, learning a new language, or playing pool in his free time.
