The data ecosystem of an enterprise comprises of a variety of legacy and modern applications. Over time, a business may decide to migrate from an existing database to save costs, enhance reliability, achieve scalability, or any other objective. This process of moving data from one place to another is known as database migration.
Although an essential step in the cloud journey of enterprises, data migration projects can prove to be very complex. They require downtime and changes in the application logic, which may lead to interruption to the data management operations. Therefore, before undertaking a migration project, it is important to understand the risks involved, the best practices of migration data from one platform to another, and the database migration tools that can help expedite the journey and mitigate the risks.
Common Reasons for Database Migration
- Upgrading to the latest version of the existing database to improve security and compliance
- Moving data to a new database to reduce cost, improve performance, and achieve scalability
- Moving from an on-premise database to a cloud-based database for better scalability and lower costs
- Merge data from several databases into a single database for a unified data view post-merger
How Database Migrations Work
Often a small component of a bigger application modernization project, database migration is a multi-step process that starts with the assessment of the source system and finishes at testing the migration design and replicating it to the product build.
Let’s take a look at the different steps that together comprise the process of migrating from one database to another.
1. Understanding the Source Database
This is the first step of the process where you need to understand the source data that will populate your target database. Here are the questions that you should be able to answer about your source database:
- What is the size of the source database? The size of the database you are trying to migrate and the number of schemas and tables comprising it will determine the scope of your migration project. This will also determine the amount of time and computing resources required to copy and transfer the data.
- Does the database contain ‘large’ tables?’ If your source database contains tables that are larger than a hundred gigabytes and have millions of rows, you might want to use a tool with the capability to load data in parallel.
- What kind of data types will be involved? If you are migrating data between different database engines, such as Oracle to PostgreSQL, Oracle to MySQL, MySQL to PostgreSQL, etc., you will need schema conversion capabilities to execute your data migration project successfully.
2. Assessing the Data
This step involves a more granular assessment of the data you want to migrate. You would want to profile your source data for inconsistencies, duplicate values, or incorrect information. Data profiling at an early stage of migration will help you mitigate the risk of delays, budget overruns, and even complete failures. You will also be able to define data quality rules to validate your data and improve its quality and accuracy.
3. Converting Database Schema
Heterogeneous database migrations that involve migrating data between different database engines are relatively more complex than homogenous migrations. These include converting the source database schema as well as other objects, such as views, functions, and stored procedures to a format compatible with the target database.
While this task can be performed manually, it is often very resource-intensive and time-consuming. Therefore, using a data migration tool with database schema conversion capability can help expedite the process and migrate data to a new database that is better capable of handling workloads, scalable, and more secure.
4. Testing the Migration Build
It’s a good idea to adopt an iterative approach towards testing a migration build. You can start with a small subset of your data, profile it, and convert its schema instead of running a full migration exercise at once. This will help you ensure that all mappings, transformations, and data quality rules are working as intended. Once you have tested a subset, you can increase the data volume gradually and build a single migration workflow.
5. Executing the Migration
Since data migration projects involve download, most companies plan for them when they can afford downtimes, e.g., on weekends or a public holiday. However, as downtime windows become shorter, it has become more important than ever before to plan database migrations in such a way that interruptions to everyday data management processes can be minimized or even eliminated altogether.
This can be achieved with database migration tools that offer data synchronization or Change Data Capture (CDC) functionality. Using these tools, you can perform the initial load and then capture any changes that take place during or after the initial load.
Once all the data has been migrated to the new database successfully, a retirement policy needs to be devised for the old database, if required. In addition, systems need to be put into place to validate and monitor the quality of the data transferred to the target database.
Expedite Database Migration with Astera Centerprise
Migrations that are not completed on time can prove to be costly, both in terms of revenue and reputation. To expedite data migration projects and minimize the risk of failure, your business needs an enterprise-grade tool that can automate the repetitive tasks associated with data migration while ensuring data quality and minimum downtime.
Astera Centerprise is an end-to-end data management solution that is designed to cater to the complex data needs of businesses. When you need to migrate data between two different versions of a database engine or perform a heterogeneous migration, Astera Centerprise can help you with:
- Parallel processing engine and high availability feature that promise you optimal performance with minimal downtime
- Data synchronization capability that helps you capture changed data and save the time and processing power spent on bulk data loads
- Advanced data profiling and quality features that allow you to validate data against custom business rules to minimize data errors and inconsistencies
- Support for a range of on-premise and cloud-based databases to cater to any database migration use-case
- Drag-and-drop mapping to perform complex data transformations in a code-free manner
Interested in learning more? Watch this quick demo, download a Centerprise trial, or contact us to discuss your database migration use-case.
Originally published at https://www.astera.com on July 15, 2019.
