Online vs. Offline Database Migrations: Which Path is Right for You?

Database migrations are a necessary evil in the life of any growing application or a company. They’re often complex, stressful, and, if not handled correctly, can lead to major headaches. One of the first critical decisions you’ll face is choosing between an offline or online migration strategy. Both have their pros and cons, and the best choice will depend on your specific needs, resources, and risk tolerance.

Let's break down the key considerations and when each approach shines.

The Essentials: Shared Concerns for All Migrations

Before we dive into online vs. offline, let's cover common ground. These are things to think about no matter which migration method you choose:

• Speed and Throughput: How long d? This depends on the number of records, their size, latency between systems, network bandwidth, write capacity of your destination database, and the parallelism of the migration tooling that you will choose. Migration speed and throughput aren't simply linear calculations. Think of it like moving houses – the time it takes depends not just on how much stuff you have, but also on the size of the moving truck, the distance between houses, and how quickly you can unpack at the new location.

  Pro-tip: Put your migration host in the same region as your databases, and over-provision your destination to handle the initial surge of writes.

  
  

• Careful Planning: Always start with your lower environments (dev, QA). Run dry runs on production to simulate real-world data migration scenarios and identify any hidden issues. You don’t want surprises when you’re moving your most important data. Differences between production and lower environments are common, so be vigilant about schema and data type discrepancies.

  
  

• Testing, Testing, 1-2-3: Don't just verify functionality in the new database! Run performance tests to see how your queries and operations are performing. Changes in database technology – even version upgrades – can drastically impact performance.

  
  

• The Escape Hatch: Rollback Planning: While it's rare to actually roll back a migration, having a fallback plan is crucial for risk mitigation. It's like having a parachute – you may never use it, but you’re darn glad it’s there.

  
  

• Data Integrity Validation: Validate your data with checks like count comparisons, full database/table hashes, and spot checks. Find that balance between risk, downtime and migration duration. Sometimes, a combination of methods is need. Note that most off-the-shelf tools don’t help you validate, placing this burden on the user.

  
  

• Migration Resumability: Can you stop and resume the process, or do you need to start over? This has massive implications for how you plan your migration window, so think about this carefully.

  
  

• Indexes: A Hidden Time Sink: Migrations can be a fantastic opportunity to optimize your indexes. It may even be required, as some databases need different indexing strategies, e.g. Cosmos DB and MongoDB. Should you create indexes before or after the data copy? For small datasets, it doesn't matter as much. But for larger datasets, you are best to build them after the initial copy to avoid write amplification and make sure that index sizes stay on the smaller side.

  
  

• Cost: Mission-critical migrations take time, effort, and money. While it may be tempting to consider them a one-off expense, it’s a project with many variables, that can easily stretch into months. The more variables you can identify and control, the smoother the project will run. We recommend opting for an optimized self-service migration tool that can help you iterate fast. In our experience, this helps reduce project timelines from months into weeks.

  
  

Offline Migrations: The "Big Bang" Approach

Offline migrations involve taking your source system offline, moving all the data, and then bringing the new system online. Just like backup and restore. It's straightforward in concept but comes with some caveats.

When Offline Migrations Work Best:

• Lower Environments: Ideal for development, testing and QA environments.

• Tolerance for Downtime: You can afford a service interruption.

• Minimizing Variables: You want to avoid the added complexity of online migrations.

• Smaller Datasets: Typically suitable for under 100GB or under a million records/documents.

Online Migrations: The Seamless Transition

Online migrations strive for zero or minimal downtime by migrating the data while the source system remains active. Typically they involve an initial data copy followed by a streaming changes in real-time from the source to the destination. This is ideal for applications that can’t tolerate service disruptions.

When Online Migrations Work Best:

• Minimize Downtime: Essential for mission-critical applications, SaaS products, e-commerce platforms, or anywhere a prolonged outage has severe financial implications.

• Large Data Sets: Suitable for 100s of GB or 10s of millions of records or more.

• Testing In Parallel: Allows running the old and new systems concurrently for pre-cutover validation.

Reference: Common Migration Tooling for Migrating MongoDB, Azure Cosmos DB, or AWS DocumentDB

• mongodump + mongorestore: A reliable offline MongoDB solution that can process multiple namespaces in parallel.

• MongoDB Live Migrate: A good option for live migrations to MongoDB Atlas, but with limitations.

• MongoDB's mongosync: A newer tool for MongoDB replication and online migrations. It offers a high level of parallelization and a REST interface, and only works for native MongoDB databases 6.0+.

• MongoDB's mongomirror: As an predecessor of mongosync, it supports online migrations for native MongoDB databases, and supports older MongoDB versions going back to 2.6, but it has many limitations such as single threaded CDC and it doesn’t work with sharded clusters.

• Azure Data Factory & AWS DMS: Easy-to-use web-based solutions for Azure and AWS, respectively. As managed solutions, they are not available for local deployments, require specific firewall configuration, have performance and other limitations.

• Kafka + Debezium: A very flexible solution that requires custom code, orchestration and Kafka infrastructure.

• 3rd Party ETL Solutions (Airbyte, NiFi, Fivetran, etc.): Generally complex, not optimized for database migrations. They carry performance, cost and data security limitations.

• Dsync: A single binary that enables online migrations between different databases by seamlessly incorporating both initial data copy and CDC (change data capture) for replicating changes from the source to the destination. Dsync parallel design also helps with accelerating the initial data copy by 10x for large data sets, thus allowing users to execute a simple offline migration where otherwise they would have to do it online.

  
  

Making the choice

Your migration strategy should align with your specific circumstances and requirements. Consider online migrations when downtime must be minimized and your dataset is substantial. Opt for offline migrations when simplicity and risk reduction take precedence, particularly with smaller datasets or non-production environments. If you're not sure, try the offline approach first.

The landscape of migration tools continues to evolve, with solutions ranging from cloud provider offerings like Azure Data Factory and AWS Data Migration Service to specialized tools like dsync. Each brings its own strengths and limitations, making it crucial to evaluate them against your specific needs, infrastructure constraints, and performance requirements.

Remember that successful migrations aren't just about moving data – they're about ensuring your application continues to perform optimally while maintaining data integrity throughout the process. Taking time to plan, test, and validate your migration strategy will pay dividends in the form of a smoother, more reliable transition.