Database Schema Migration: Propagation-Driven Sync

As your application evolves with the changing business needs and user demands, schema migration becomes very essential. However, due to the complex logic in the schema, such as intricate table relationships and constraints, the process can be quite challenging. Strategic planning and execution are important to ensure that the database structure aligns with the application's needs without causing errors.

In this blog post, you'll explore the database schema migration best practices and some popular tools that can help you navigate this process efficiently.

What is Database Schema Migration?

Schema migration is the process of updating a database structure from its current state to a new desired state. This includes adding, altering, or removing tables, columns, or constraints to reflect new requirements in the database schema design. Schema migration is essential for maintaining the performance of a database and adapting to the dynamic needs of your application.

Without a well-defined process, inconsistencies can arise between the application data model and the schema, leading to errors and application downtime. You can use any of the several available, secure schema migration tools that let you manage the changes systematically, preserving data integrity and minimizing disruptions.

Reasons For Schema Migration in Databases

Schema migration is essential for several reasons, a few of them are:

Adapting to New Features

When you introduce new functionality in an application, the database schema should be revised to meet such changes. For example, if an e-commerce bookstore introduces digital downloads, then it must update the database schema to add new fields for download links and file sizes.

Performance Optimization

If the volume of data increases, it may take a significant amount of time to execute some of your queries. You can optimize query performance and overall database efficiency by modifying the schema, like adding indexes and partitioning tables.

Database Platform Transitions

If you migrate data from one database platform to another, schema migration is necessary to maintain compatibility with the new system. For example, migration from MySQL to PostgreSQL requires schema modifications in data types or indexes to ensure that the database functions efficiently on the new platform.

Ensuring Data Integrity

Schema migrations may be necessary to enforce constraints and preserve data integrity. For example, to ensure every customer_id in an orders table corresponds to a valid entry in a customer’s table, you may need to add a foreign key constraint. These changes guarantee only valid data is entered into the database and prevent duplicate entries or invalid data relationships.

Improves Security 

Fixing security issues or introducing new features requires schema changes. This may involve column-level encryption, data masking, or more rigorous access controls. These schema migrations assist in strengthening the security of your database and help you comply with data privacy laws.

Bug Fixes

Bugs in database design can cause incorrect data storage, retrieval issues, or unexpected application failures. Correct schema migration can help you fix these problems by correcting column data types, adding missing fields, or restructuring tables.

How to Plan Database Schema Migration?

Here's a step-by-step approach to help you plan your database schema migration effectively.

Step 1: Assess the Current Schema

First, you must examine the current state of your database schema. This involves evaluating the tables, columns, and relations between different data records in the database. Based on this, you can decide what modifications you want to introduce in the schema. Such an approach ensures that you do not overlook any data or dependencies during schema migration.

Step 2: Define Your Migration Objectives

On the basis of results obtained in the first step, you can define the changes that you want to make to your database schema. Adding or removing tables and columns and updating relations are some of the revisions that you can perform during the database schema migration process. Having a strategy beforehand enables you to update your schema in a highly efficient way.

Step 3: Create a Data Backup

Before starting the migration process, create a backup of your entire database structure. This helps you prevent data loss on the occurrence of any undesirable event, such as the accidental deletion of an important column. To create data backups, you can opt for suitable automated solutions according to your organization’s data retention policies. You can also use version control tools like Git to track and revert changes made to your database schema.

Step 4: Test 

To ensure the success of schema migration, first test the migration in a staging environment that is similar to your original setup. During this process, examine and rectify any issues, like performance bottlenecks or compatibility problems. You should also check that your data is not lost and that your application works correctly with the updated schema.

Step 5: Implement the Changes

You can now make the modifications in your database schema in the end-user environment. To avoid failures like system crashes, you should introduce the changes incrementally in multiple steps. If you are deleting some data records, you should adopt a deprecated approach by phasing those data points gradually. This allows you to properly adjust application code according to the changed schema.

Step 6: Validate

Finally, you must validate the tailored schema to verify the success of your database schema migration procedure. You can do this by using validation techniques such as data type, code, consistency, and format check. Even after validation, you should periodically monitor the database schema to ensure the proper functionality of your application.

Schema Migration Best Practices

Some of the essential database schema migration best practices to consider:

Document Your Changes: Without documentation, changes can be hard to revert. Keep a log of all schema changes, including new tables, changed columns, and deleted entities. This will help you debug issues faster.‍

Use version Control: Use a version control system like Git to manage your database schema and migration scripts. This lets you monitor changes, collaborate with your team, and roll back to earlier versions if required.‍

Implement Rollback Procedures: Before you start migration, have a rollback plan in place. Test the rollback scripts to ensure that you can restore the database to its previous state without data loss or corruption.

Automate Wherever Possible: Automation speeds up schema migration and reduces human errors. By automating repetitive tasks like schema validation, you can free up time for your team to focus on more complex issues, improving the reliability of the migration process.

Collaborate and Communicate: Encourage transparent communication and collaboration among all stakeholders involved in the schema migration. Share updates, discuss potential risks, and coordinate efforts to ensure a smooth and successful migration.

Use Cases For Database Schema Migration

Some critical use cases for database schema migration across various domains are:

Healthcare

The healthcare sector requires accurate patient records for regulatory compliance. For instance, in your clinic, you need to update your database schema to incorporate more fields for electronic health records (EHR) or to enable interoperability with other healthcare systems.

This often involves adding tables for patient history, lab results, and treatment plans. Through effective schema migration, you can enhance patient care and improve operational efficiency.

Logistics

In logistics and supply chain management, schema migrations are necessary for optimizing operations and visibility across the supply chain. For example, a logistics company might need to update its database schema to include real-time tracking features like GPS coordinates for vehicles or IoT sensor data for temperature-sensitive shipments.

It can be done by creating new tables to store delivery timestamps, route optimization parameters, and customer feedback metrics. This helps the company streamline its workflows, reduce delivery times, and improve customer satisfaction through better communication and transparency.

E-commerce

E-commerce platforms rely heavily on efficient database schema management. The dynamic nature of online retail necessitates frequent updates to the database structure. This could be adding new columns for product attributes or modifying tables to accommodate promotional initiatives. 

For example, an e-commerce site might need to add a new field to the product catalog or update the order table to support new payment gateways. Database schema migration tools effortlessly facilitate this transition from the current state to the desired state.

Finance

In financial institutions, you need to frequently modify database structures to increase security or introduce new financial products, such as personalized loan offerings. You can reorganize tables to hold transaction logs, customer risk assessments, and fraud detection parameters.

For example, if a bank launches a new credit scoring model, changes have to be made in the existing tables to accommodate additional risk factors. Schema migration ensures that these updates happen smoothly, facilitating uninterrupted financial operations.

Database Schema Migration Tools

Some of the popular database schema migration tools:

Airbyte

Airbyte, an AI-powered database migration tool, empowers you to move data across diverse platforms. The platform offers an extensive catalog of 550+ pre-built connectors to various data sources and destinations, facilitating effortless data transfers. With Airbyte, you can set up automatic schema change propagation to update your destination based on changes in the source schema. Internally, Airbyte uses a process called DiscoverSchema, which runs in the background to compare the old schema with the new one and propagates the modifications. 

Once configured, Airbyte performs schema checks for Cloud users every 15 minutes and every 24 hours for Self-managed users. These regular checks ensure that your data remains accurate and up-to-date. 

Bytebase

Bytebase is a robust database schema migration tool that enables you to streamline and secure the process of managing database changes. It supports diverse databases and offers features like schema drift detection and schema syncing. By integrating Bytebase with GitOps, you can conduct version-controlled schema changes. Its intuitive web GUI provides review, deployment, and rollback of database changes.

Liquibase

Liquibase is a database schema change management tool that allows you to track, version, and deploy database changes. It lets you define changes in varied formats, including XML, YAML, and JSON. Additionally, Liquibase enables you to integrate with CI/CD pipelines, facilitating automated and continuous delivery of database changes. 

Atlas

Atlas is an open-source, language-agnostic tool designed for migrating database schemas using modern DevOps principles. It enables you to define your desired database schema in SQL, HCL, and many other programming languages. Atlas then compares the current database state to the desired state and automatically generates and executes a migration plan.

Common Mistakes People Make (+ Solutions)

Here are some common mistakes involved in schema migration, along with the possible solutions to overcome them:

Improper Planning

Migrating a database schema without a proper plan can lead to unforeseen issues. A lack of understanding of the existing schema, dependencies, and potential impact on applications can result in error-prone migration processes. 

Solution: Thoroughly analyze the existing schema, dependencies, and application requirements before starting the migration. Create a detailed migration plan that outlines each step, including data backup, schema changes, and rollback procedures.

Inadequate Testing

Without fair testing, errors in schema migration can go undetected, resulting in data inconsistencies and application failures. This can result in expensive and time-consuming fixes that can severely affect your business functionality.

Solution: Test the migrated schema in a staging environment that mirrors the production environment. You should perform extensive testing, including unit tests, integration tests, and performance tests, to detect potential issues and ensure a smooth migration.

Ignoring Downtime

Schema migration can cause temporary downtime in business operations, as applications may need to be taken offline to implement changes. This can disrupt users' access to critical services, causing inconvenience. If not planned properly, these migrations can also result in extended outages.

Solution: You should break large migrations into smaller, incremental steps to reduce the risk of prolonged outages. Schedule the migration during low-traffic periods to reduce the impact on users and communicate with stakeholders about expected outages in advance.

Schema Drift and Inconsistencies

Schema drift occurs when changes to the database schema are not applied uniformly across all instances. This lack of synchronization causes issues with your applications. For example, imagine a company adds a new column to the database but doesn’t sync this change across all environments. This can result in errors when other teams or applications access the data, expecting the old schema structure.

Solution: Adopt a robust schema management process that includes version control, automated deployments, and schema validation. You can also use schema comparison tools like dbForge Schema Compare to identify and resolve differences between schemas.

Not Considering Backward Compatibility

Backward compatibility ensures that old versions of the application can still work with the updated database schema, facilitating safer rollouts. Without backward compatibility, older versions of the app may break when the schema is updated, causing disruption to the users.

Solution: Test interactions between applications and the new schema to ensure that the new schema is backward compatible with existing applications. You should avoid dropping columns, tables, or indexes that the current application might depend on. For example, instead of renaming columns or tables directly, you can add new ones and phase out old ones gradually.

Conclusion

Database schema migration is important for keeping up with your evolving data model. This article guides you through the key reasons behind the schema migration and the best practices to help you simplify the process. Further, you've examined common mistakes and their possible solutions. By following these guidelines and choosing the right tools, you can perform a smooth and successful schema migration.