What are the Types of Database Migration? [+Concepts and Strategies]

Expanding businesses and evolving technologies often necessitate the modernization of data management systems. As your company grows, your data infrastructure must also scale accordingly to handle the increased data volumes and complexity. This process frequently involves moving data from one database to another, known as database migration.

However, the process of database migration involves careful planning, risk assessment, and strategy formulation to ensure a smooth transition. Let’s look into the different concepts and strategies associated with database migration.

What is Data Migration?

Data migration is the process of transferring data from one system, format, or environment to another. It comes in handy every time an organization makes a new system installation or upgrade existing technology so that data present on the old system have to be transferred to the new system. It is also crucial that the data should be transferred accurately and securely so that it does not lead to loss or corruption of the data nor does it hinder business operations.

Key Scenarios Where Data Migration is Needed:

• Database migrations: Upgrading to a new database or changing the database structure.
• System upgrades or replacements: Moving from legacy systems to modern platforms.
• Cloud migration: Transferring on-premises data to cloud-based systems.
• Mergers and acquisitions: Consolidating data from different organizations.
• Data center relocation: Moving data from one physical location to another.

Types of Database Migration

There are different types of database migration that you can consider for your business.

1. Storage Migration

One of the common reasons for storage migration is to upgrade storage equipment to more sophisticated modern storage equipment.

Examples of such migrations include moving data

• From mainframe computers to cloud storage
• From HDDs to faster, more durable SSDs

It’s the pressing need for technology upgrades rather than the lack of storage space that drives the need for storage migration. Typically, it doesn’t alter the content or format of data. The steps involved in this type of migration include:

• Data Validation: This ensures the accuracy, quality, and integrity of data. It confirms that the data on the target system is the same as that on the source system. Data validation helps identify and address any errors or inconsistencies in the data.

• Cloning: Cloning refers to creating an exact replica of the data. This is a crucial step to preserve data integrity during the migration process. By maintaining a clone, you can resolve any issues that may arise during the migration without losing data.

• Data Cleaning: The purpose of data cleansing is to remove or correct any incomplete, incorrect, inaccurate, and irrelevant data. This will help improve the quality and efficiency of the data in the new storage system.

• Redundancy: With data redundancy, you will have two or more copies of the data. This precautionary step helps prevent data loss in case of any error or failure during the migration process.

The challenges associated with this type of migration involve downtime, incompatibility issues, and initial performance issues of the new system with the existing data setup.

Among the benefits of storage migration is that it helps reduce the data migration time. There is no need for additional licenses or software, and the source storage system’s configuration needs no change.

2. Application Migration

When an organization undergoes a change in application software or changes an enterprise software vendor, the data must be moved from one computing environment to another.

The challenges in application migration majorly arise from the use of distinctive data models and different data formats between the old and target infrastructures. You must ensure that the data is communicable between the software when undergoing this type of migration. Application Program Interfaces (APIs) from vendors can help protect data integrity. Vendor web interfaces can be scripted to facilitate data migration.

3. Data Migration

A database isn’t just a place to store data; it also provides a structure to organize information in a specific way. Databases are managed through database management systems (DBMS). A database migration is when you move from one DBMS to another or upgrade from the current DBMS version to the latest version.

Here are some challenges associated with database migration:

• Incompatibility: Moving from one DBMS to a different provider can be challenging if the source and target databases support different data structures. The task gets more complicated when moving data from legacy databases like IDMS, IMS, or Adabas.

• Downtime and Disruption of Operations: Migrating a database often involves taking the system offline, which can disrupt business processes.

• Complex Data Structures: When migrating from one system to another, you may have to deal with complex data structures that must be solved. This is to ensure the data fits into the new system’s structure.

4. Business Process Migration

A business process migration is usually driven by mergers and acquisitions, business optimization, or reorganization. The reason for this could be the need to enter new markets or remain competitive.

Usually, companies maintain their vital information and applications within a data center. This is a physical place with IT technology and equipment rather than a digital one. When a business wants to move all of its digital property to other parts of an operating facility, business process migration may be a viable solution.

Since this type of migration involves merging different business processes, it often includes integrating disparate systems, which can be a complex, time-consuming process. Any unforeseen complications can result in increased costs and budget overruns. It’s also challenging to ensure the migrated processes are at par with the performance and quality of the old system.

5. Cloud Migration

Cloud migration is an increasingly common type of migration. The driving factors for this could be the need for improved scalability, flexibility, or cost savings.

Gartner predicts that by 2024, the cloud will dominate the ever-growing number of IT decisions and attract over 45% of IT spending.

Depending on the differences between the source and target locations and the data volumes, migration may take anywhere from 30 minutes to months or even years. An example of cloud migration is when you shift from a local server setup to a service like AWS, GCP, or Microsoft Azure.

Challenges with cloud migration involve:

• Data Security and Privacy: Migrating data to the cloud can expose it to new vulnerabilities. Your primary concerns will be about data breaches and privacy issues.

• Compliance Issues: Ensuring industry regulatory compliance can be more complex in a cloud environment.

• Legacy System Compatibility: Legacy systems may not be completely compatible with cloud environments, leading to data loss or corruption during the migration process.

• Skill Gap: Your team may not have the skills required to manage cloud infrastructure and services. You may have to train or hire new staff.

6. Data Center Migration

Data center migration refers to moving the entire database from one physical location to another. It could also involve the movement of data from an old data center infrastructure to new infrastructure equipment at the same physical location.

The need for this type of migration arises with organizational restructuring, mergers, or seeking better infrastructure.

Some significant challenges associated with data center migration involve:

• Data Loss and Corruption: There’s a possible risk of data loss or corruption during the relocation process.

• Cost Overruns: Data center migrations can get expensive, especially when there are unforeseen circumstances.

• Logistical Complexity: Physically moving hardware to set up in a new location can be a complex, resource-intensive process.

Database Migration Types on the Basis of Extent Of Migration

1. Full Migration

It Involves transferring the entire data from one source to any destination. This requires a significant amount of time and resources as it includes complete replication of existing data. 

This type of migration is usually beneficial if you are moving from a legacy system to a cloud platform or any other mjodern platform for more scalability and efficiency. 

Benefits:

• Simplifies future data management since all data is centralized in the target system.
• Ensures complete data continuity.

Challenges:

• Requires significant planning and testing, especially if the dataset is large.
• Can lead to downtime during the migration process, which impacts business operations.

2. Partial Migration

This involves migrating selected portions of data from source to destination. Only a portion of the data is migrated, based on certain criteria such as time, relevance, or specific business needs.

It is often used when only active or relevant data is needed in thenew system or when the new system is gradually phased in.

Benefits:

• More manageable in terms of time and effort.
• Reduces costs by transferring only necessary data.
• Minimizes the risk of transferring outdated or irrelevant data.

Challenges:

• Complexity in deciding what data to move and what to leave behind.
• Potential issues with legacy systems needing to be maintained for older data access.

3. Incremental Migration

Phases or chunks of data is migrated over time instead of all at once. It involves transfering data incrementally in order to populate the new system but still operate the old system.

It is often used when there is a need to minimize downtime and ensure business continuity during the migration.

Benefits:

• Minimizes operational disruptions by migrating data in small batches.
• Offers better error handling and testing, as each batch can be validated before moving to the next.
• Allows rollback if any issues arise in the migration process.

Challenges:

• Can be more time-consuming compared to full migration.
• Data consistency must be carefully maintained across both systems during the processs

4. Pilot Migration

A trial migration, where only a small portion of the data is transferred to test the process before a full migration. The subset chosen for pilot migration needs to be representative of the broader dataset to provide valuable insights.

This type of migration is used to evaluate the migration strategy, processes, and tools before a large-scale migration.

Benefits:

• Reduces risks by identifying potential issues before full migration.
• Allows thorough testing of the new system with real data in a controlled environment.
• Provides a learning opportunity to refine the migration strategy.

Challenges:

• The pilot system may need to be discarded or reset for the full migration.
• Data from the pilot may not represent all complexities of the full dataset, requiring further adjustments later.

Different Migration Strategies

The different approaches to database migration involve

1. Big Bang Database Migration

This strategy of migration involves transferring all data from a source system to a target database in a single operation at a single point in time. It is often performed over a weekend or a scheduled downtime period.

While the Big Bang database migration strategy is relatively simple and occurs in a time-boxed event, the tradeoff is downtime. This could be undesirable if you run your systems 24/7 in your organization.

If you work for a software company and want to migrate your entire customer database to a new, more advanced system, consider using Big Bang data migration. You can plan the migration over a weekend when system usage is at its lowest. With the data backed up and a thorough plan (in case of any failures) in place, you can manage to complete the migration within the scheduled downtime.

2. Trickle Database Migration

With an agile-type approach to database migration, a trickle migration breaks down the process into small sub-migrations, each with its own scopes, goals, and deadlines. This makes it easier for the database migration team to confirm the success of each phase.

If any sub-process falters, only the failed process will require re-work. The subsequent runs can be improved by utilizing the knowledge obtained from each failure. This is one of the reasons why it’s less prone to unexpected failures.

However, the drawback of trickle database migration is that it takes more time. It requires running two systems simultaneously, consuming more effort and resources.

If you work for a life insurance company requiring a database migration without interrupting your 24/7 operations, this is an appropriate choice. You can opt for trickle migration, breaking down the process into multiple phases, each focusing on different data sets while ensuring continuous availability. This also allows the data team to test and validate each phase independently, hence reducing the risk of major failures.

3. Zero-Downtime Database Migration

This migration strategy replicates data from the source database to the target database. With zero-downtime database migration, you can access the source database and operate on it while the migration is in process.

The benefits include faster migration, reduced business disruption, and minimal cost, especially when considering all-hands migration efforts and business impact.

If you work for an e-commerce platform looking to migrate your substantial product database without affecting round-the-clock online shopping services, consider employing a zero-downtime migration strategy. The data team can replicate data to the new database while keeping the old database operational. It will help complete the migration without any disruption to the online services.

Database Migration Process

The database migration process involves certain stages, each critical to successfully transitioning from the old to the new database system. Here’s an overview of the steps involved:

1. Pre-migration Planning

Planning involves the evaluation of your existing datasets and the careful design of a migration plan. This stage can be divided into four steps:

1. Refine the Scope: Filter out any excess data to define the minimal amount of information required to run the system effectively. This will require a high-level analysis of source and target systems while consulting data users who will be directly impacted by the changes.

2. Assess Source and Target Systems: Thoroughly assess the current system’s operational requirements to understand how they can be adapted to the new environment.

3. Set Data Standards: This allows your team to spot any issues in each phase of the migration process and avoid unforeseen circumstances in the post-migration stage.

4. Estimate Budget and Set Realistic Timelines: Select the strategy, estimate the resources required for the project, and set schedules and deadlines. 

2. Data Inspection

Inspect the scope of the data you want to migrate with data auditing and profiling. This aims to identify data quality issues, detect possible conflicts, and eliminate duplications and anomalies before migration.

Auditing and profiling are time-consuming and labor-intensive tasks; consider employing automation tools for large projects.

3. Data Backup

While this stage isn’t mandatory, backing up all the data to be migrated is a best practice of database migration; the backup guards against any migration failure that may result in data loss.

4. Migration Process Design

The migration process design specifies the migration testing procedures, acceptance criteria, and other personnel responsibilities.

If your project involves large data volumes and complex data flow, consider alternative database transfer solutions, such as hiring an ETL developer, data engineer, or third-party ETL tools.

5. Execute and Validate

This stage is when the migration actually happens. The duration of this stage will depend on the data volumes involved and the data migration approach chosen.

If you choose the trickle approach, it is essential to monitor and validate the process to see if there are any signs of failure and downtime to the old system. Validating the migration process helps ensure the data migrated to the new environment is complete and viable for business use.

5. Post-Migration Audit and Decommission

The results should be validated with key business users before launching the migrated data in production. This ensures the information has been correctly transported and logged.

After this post-migration step, you can shut down and decommission the old system.

What are the Associated Challenges with Database Migration?

While database migration is vital for technological growth, it has its risks and challenges, such as:

• Data Loss: Critical data may be lost or corrupted during database migration. This necessitates taking a backup and planning the migration diligently with help from professionals.

• Downtime: Database migration can take a long time, from a few months to several years. The process may prolong upon encountering network blockages that can affect transmission times. Extended downtime during migration may disrupt business operations.

• Data Security: Migration processes can expose your data to security vulnerabilities. The associated risk of data breaches may result in the loss of confidential information, leading to potential legal and reputational damage.

• Budget Overruns: Prolonged migration or unexpected complications can cause budget overruns. Personnel and vendor software charges may override budgeted amounts, leading to financial strain on the organization.

• Compatibility Issues: Incompatibilities between the old and new systems can result in functional problems. This can cause disruptions to business processes, requiring additional time and resources to resolve.

What are the Best Practices for Database Migration?

In database migration, it’s crucial to ensure a smooth, efficient process with minimal risks. Here are some best practices and strategies for Data Migration that can help achieve this:

• Assign a dedicated migration team to manage the project and consider hiring data migration specialists.

• Set the parameters (object types, source objects in scope, connection parameters, etc.) of your database migration project.

• Analyze your current data and determine how much data you need to move. Consider data cleaning to ensure that only quality and useful data is migrated.

• Multiple teams must give their input to the data migration process. Communicate the entire data migration process to them.

• All data must be profiled before writing mapping scripts.

• Allocate considerable time for the design phase as it has a high impact on the success of the project.

• Always back up the existing data before starting the migration process.

• Select appropriate migration tools like Hevo Data or database transition services for your specific requirements.

• Perform testing at each phase, especially throughout the planning and design phases. Testing is also critical during implementation and maintenance.

• Plan the migration to minimize downtime, which is essential for business-critical systems.

• Don’t be in a hurry to switch off the old platform. If the first attempt at data migration fails, a roll-back will be necessary.

Choosing the Best Database Migration Service

There are several database migration tools available in the market, each with its unique features and capabilities. However, for a real-time, scalable solution, consider using Hevo Data for your database migration needs. Here are some benefits associated with Hevo:

• Real-Time Updates: Hevo supports real-time data migration, populating your databases with the latest updated data. This enables effective data-driven decision-making.

• Source and Target Database Support: The availability of 150+ connectors helps simplify the process of setting up a data migration pipeline between any two databases.

• Transformation: Hevo offers Python-code-based transformations and preloaded transformations with a drag-and-drop interface to simplify data transformations. To transform data loaded in the warehouse, you can use its Postload transformation capabilities.

• Scalability: With a fault-tolerant architecture, Hevo data pipelines function with minimal latency and zero data loss. Hevo scales horizontally with growing data volumes and an increasing number of sources. It can handle millions of records per minute with negligible latency.

• Data Recovery: To overcome the risk of data loss, Hevo maintains an encrypted backup of your last three days’ data for webhook and log-based sources.

• Security: Hevo compiles with CCPA, GDPR, HIPAA, and SOC2, ensuring the privacy and confidentiality of your data.

• Support: Hevo offers live chat with their support team and round-the-clock help for your migration needs. Other support options include email and voice call options.

Best Data Migration Tools in 2024

It is crucial to choose the right Data Migration Tool in order to streamline your migration process. Here I have listed few industry-leading data migration tools for you to consider.

1. Hevo
2. Fivetran
3. Matillion
4. Stitch
5. AWS Data Pipeline
6. Integrate.io
7. IBM Informix
8. IRI NextForm
9. SnapLogic
10. Informatica PowerCenter

To know more details about these tools, check out our blog on 10 Best Data Migration Tools of 2024

Final Thoughts

Database migration is a complex yet essential process required for improving data management, modernizing IT infrastructure, and ensuring your business remains competitive. By understanding the various types of migrations—storage, application, data, business process, cloud, or data center migration—you can successfully execute a database migration project. It’s equally important to choose the appropriate strategy that aligns with your business’s needs and goals. Create a successful data migration team with the right structure. Explore more at Team for Data Migration.

But as the volume of data increases, you need a permanent solution for tackling data silos and making data-driven decisions through data analytics. Here’s where Hevo Data, our automated data pipeline platform can help you.

Sign up for a 14-day free trial and simplify your data integration process. Do check out the pricing details to understand which plan fulfills all your business needs.

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