Database Migration Checklist - Moving to PostgreSQL

Migrating to a PostgreSQL database is a complex process, even if you’ve done it before. Moving large amounts of data spread across multiple systems can often lead to downtime and frustrated users.

For most, a database migration requires careful planning; some will even bring consultants to assist. But is that really necessary? In this post, you’ll find a database migration checklist that helps you transition in a DIY fashion. The checklist goes through the preparatory steps, the migration process, and post-migration testing. If this is your first migration, the list will help you plan, execute, and validate migrations while decreasing common risks. Bookmark this article to keep the checklist at hand.

Before you get started

Smaller teams generally face more issues when migrating databases. Due to budget limitations, founders will often lack dedicated database engineers. This makes them fully responsible for infrastructure management. And as many “done is better than perfect” entrepreneurs come to realize, moving from MySQL to Postgres is a complex task that requires a different approach.

Without proper planning, migrations can quickly spiral out of control. Schema variations, incompatible data types, indexing differences - even minor mistakes in the details can lead to corrupted records. Not many founders will know, for example, that MySQL allows unsigned integers, while PostgreSQL does not. Overlooking a detail like this can break user IDs.

Dependencies between services can add to this complexity. If an API refers to a table in the process of migration, you may end up with inconsistencies. If uptime is affected during the migration, your project might lose revenue and customers.

The same is true for Cloud databases. A migration that involves replication, adjustments in storage, or server configuration makes the process more complex. And, similar to the above, this needs to be addressed with utmost care. 

All these components make a data migration plan template essential for the process itself. A template where every step is documented, including backups, rollback procedures, and all the required testing steps. They help designate and track team responsibilities, which makes the migration more predictable.

Pre-Migration Planning and Assessment

Before a migration takes place, we’ll make a roadmap and understand what steps will need to be taken. This will align your team and identify risks ahead of time. For early SaaS teams, it’s best to divide these steps into three categories.

1. Database Inventory and Dependency Assessment

2. Schema and Storage Planning

3. Stakeholder and Success Criteria Planning

Doing so makes the process more manageable and gives a better overview.

Database Inventory and Dependency Assessment

Start by creating a full inventory of your databases and mapping out how your product’s ecosystem interacts with them. Creating a map like this ensures that all data, tables, and relationships are accounted for, reducing risk down the road.

Checkpoints for this assessment:

Databases/tables: List every database instance that your app relies on, including development, stage, and production environments. Add all relevant tables, indexes, and stored procedures. 

Locate dependent services: Identify the APIs, apps, dashboards, and cron jobs that regularly interact with your database(s). For example, payroll services may use certain tables for invoicing. Map these dependencies to not disrupt workflows during the migration process.

Determine data volumes: Note the number of rows, size, and growth patterns for each relevant table. Larger tables might need to be scanned for batching or duplication during the migration.

Data categorization: Divide your tables into those critical to your operation, versus those that can handle downtime or temporary issues. This enables you to prioritize data when migrating, reducing risk to services that are critical.

Relationships between tables: Document relational dependencies between tables and check for foreign key violations.

Document automated workflows: Review background tasks, scheduled scripts, and ETL jobs that may interact with the database. Highlight processes that can be stopped or adapted temporarily during the migration. 

This preliminary assessment helps you get a bird ’s-eye view of your current database environment and its relationships. This can help prevent issues and help you understand how to prioritize.

Schema and Storage Planning

Schema and storage prep ensure that your current database schemas translate into those of PostgreSQL. Each database has a different schema structure and, if this step is overlooked, the transition may lead to mismatches and storage problems. This part of the plan has some key elements to consider:

Data type highlight: MySQL and PostgreSQL process certain queries in a different way. There are many instances like this one, and using an LLM can be really helpful here. Some examples include:

MySQL ENUM → PostgreSQL VARCHAR with CHECK constraints

MySQL TINYINT(1) → PostgreSQL BOOLEAN

MySQL UNSIGNED INT → PostgreSQL BIGINT or adjust constraints

Index & constraint changes: Indexes and constraints are handled differently between databases. For instance, composite indexes could require reordering or syntax adjustments. Map out which indexes need to be recreated or adjusted post migration to ensure performance is not affected.

Sequences and default values: MySQL’s AUTO_INCREMENT corresponds to sequences in Postgres. You will need to create these sequences manually and make sure they align with the current data to avoid primary key collisions.

Batching large tables: A good rule of thumb for large tables is to plan a partitioning strategy. This means splitting the data into batches to reduce downtime and prevent the server from being overwhelmed during the migration.

Removing old data: Locate old or irrelevant data that you can delete, and do so before the migration takes place. This is not important for smaller datasets, as these migrate faster without impacting the app’s performance.

Estimate total storage space: Make sure that your new database environment has enough space, memory, and CPU to adopt the migrated data, including additional growth for the next year. This gives you some runway to figure out post-migration issues.

By going through this second category, you make sure that the data you intend to merge is compatible with Postgres and that performance is not affected.

Stakeholder and Success Criteria Planning

The third and final category of the preparatory stage focuses on people and processes. Migrations can quickly fail if everyone involved is not aligned with the process and does not understand what success looks like.

How to prepare:

Define stakeholders and responsibilities: Besides founders, add product managers, marketers, customer support, sales, and any external partners. Give clear instruction for all the stages of the migration, and make sure all responsibilities are placed in a relevant project management tool.

Define success: Define how success looks like. Write it down and share it with relevant stakeholders. This can be different for each team and app, but a few examples could include:

-> Downtime limit (e.g. 2 hours)

-> Full row count match between databases

-> Key dashboards and reports validation

Set expectations: This is self explanatory but still good to be mentioned here. Make sure that all team members understand the migration schedule and the impact it might have on their work.

Make a rollback plan: For added security, define a rollback procedure ahead of time. Indicate which team member is responsible for which task, what backups will be restored, and how the team will verify the integrity of the data following the rollback.

Make a migration plan document: Create a shared data migration plan template to ensure everyone is taking the steps that they are responsible for, and can backtrack if issues present themselves.

Set up migration windows: Existing data should reveal low traffic periods. Take advantage of those windows to coordinate the timing of the migration. This will minimize disruption.

Aligning everyone in your team reduces human error and makes it easier to determine the success of your migration. This is especially true for founders who would regularly depend on developers for these processes.

Executing the Migration

We have now taken all the preliminary steps to plan the migration and ensure all our data is safe in case problems arise. We now proceed to the actual process, which starts with a staging migration. 

Start by copying a subset of production data to a testing environment. This should be pretty easy to do. Confirm schema mapping, data transformations, and app interactions. This is where you get to fine-tune scripts and discover hidden issues that could cause problems later on.

Once you migrate to staging, you can start with production. The transfer itself can be automated with native Postgres scripts or tools like pgloader, and DBeaver. If moving from MySQL to Postgres, make sure you check triggers, foreign keys, and constraints with care.

Just in case we didn’t emphasize it enough, make sure you audit everything:

-> Document every table you migrate

-> Manually compare row counts pre-post migration

-> Confirm data transformations

-> Log errors to review them later on

During each step of the process, you’re going to be tracking performance and app functionality as well. Some queries or dashboards may need to be optimized post-migration. Adjust wherever necessary.

Following the migration, confirm all critical workflows:

-> Compare metrics on marketing dashboards

-> Make sure that billing systems work properly

-> Ensure that product analytics are valid

Common issues during the migration process

There are several problems that may come up when migrating databases. We may sum them up as follows:

Schema incompatibilities: Missing type conversions or auto-increment sequences can break applications. Avoid this by performing a schema comparison during the pre-migration stage.

Large datasets: Migrating very large datasets at once can lead to problems. To avoid overloading the servers, break the datasets into batches that you migrate separately. 

Underestimating downtime: If you do not take the time to go through the pre-migration steps, you may find yourself with more downtime than expected. This can cause issues with revenue and user experience.

No audits: Trying to speed things up without doing a proper data migration audit could lead to missing or corrupted data.

Overthink data transformation: Manually trying to clean and normalize all data during the migration process leads to more risk. Prioritize essentials and automate where possible.

Lack of documentation: Without a data migration plan template set in place, future migrations may impact the app in a negative way. The pre-migration plan ensures this will not happen.

Post-Migration Testing and Optimization

After the migration takes place, it’s time for testing and validation. For this, you’re gonna be running queries against pre-migration benchmarks and checking all important components.

Having built a cloud migration testing checklist, you can now confirm that:

-> API calls return accurate results

-> Reporting dashboards match pre-migration metrics

-> Automations and cron tasks operate correctly

-> Optimize PostgreSQL performance by:

-> Rebuilding indexes on large tables

-> Tuning queries and database parameters

-> Monitoring server load and adjusting configuration

Finally, inform stakeholders of the results. Each department that requires data access should confirm that systems operate correctly. Following this step, document the process in any existing database migration checklist to guide your team in future transitions. You will essentially build a data migration template with comments on each step. This is important for SaaS teams as migrations can repeat when the company reaches new growth thresholds. 

Database Migration Checklist (Copyable)

Having gone through all the steps above, we can now summarize them into a ready-to-use checklist that your team can use:

Preliminary steps (Pre-Migration):

-> Create an inventory of all databases & tables

-> Document any critical dependencies and services

-> Set up the staging environment

-> Validate backups exist & restore in a testing environment

-> Audit schema differences between databases

-> Calculate storage requirements

-> Define success criteria & downtime limits

-> Assign responsibilities to team members

Schema and Data Prep (Pre-Migration):

-> Map tables & columns (data migration template)

-> Transform data types as required by the migrating database

-> Remake indexes and sequences

-> Prepare batch migration scripts

-> Remove non-essential data

Migration Execution:

-> Start by testing staging migration

-> If successful, execute production migration in batches

-> Conduct a data migration audit to track the migration process

-> Track server performance

-> Validate queries, dashboards, and apps

Post-Migration:

-> Validate the integrity of data

-> Run cloud migration testing checklist

-> Optimize queries and indexes to better manage PostgreSQL

-> Test all dependent services

-> Document lessons learned to update migration templates

Rollback Plan:

-> Restore a backup if you face errors

-> Communicate timeline and responsibilities

-> Try again after the rollback is completed

This checklist should enable you to conduct a SaaS PostgreSQL migration without facing any issues along the way.

Wrapping up

In this article, we addressed all the steps of your transition to PostgreSQL. A database migration checklist is essential when a SaaS database undergoes this process. This is because differences in query building, schema issues, and large tables often create challenges for non-technical founders.

Using the data migration template above (& cloud migration testing checklist) ensures the process is easy to follow and review later. Pre-migration prep work, execution, and post-migration improvements ensure that your app does not experience downtime or any of the common risk factors.

For teams that work with SaaS projects, these practices create a layer of safety that guides the execution of the migration process. A database migration checklist won’t require dependence on full-time devs and consultants. Do it once, and every following time will be easier.