So, you’ve got this gigantic, monstrous, interrelated, join-heavy, super-normalized SQL database powering your legacy monolith. And now, some wise soul has decided it’s time to go all-in on microservices.

But wait! Microservices aren’t supposed to share databases! And your data is like a clingy ex—everything is dependent on everything else. If you split it up, how will your services talk? How will you get any performance? Will your database start crying in a corner?

Let’s talk about how to break up your monolithic SQL database without breaking everything else in the process.

Step 1: Accept That This Will Be Painful

First, let’s acknowledge the elephant in the room: this is going to hurt.

You’re not just moving a few things around. You’re fundamentally changing how data is structured, accessed, and managed. It’s like moving from a single apartment with one Wi-Fi router to a massive house where every room needs its own signal extender.

But don’t panic! We’ll get through it, one step at a time.

Step 2: Understand Why Microservices and Shared Databases Don’t Mix

Microservices are all about autonomy. If multiple services are dipping into the same giant SQL database, then congrats! You haven’t really built microservices. You’ve just wrapped your monolith in APIs.

When multiple services share a database, you get:

• Tight coupling – Now every service depends on the same DB schema. Change one table, and you break five services.
• Scaling nightmares – If one service needs to scale, it’s still tied to the performance of that single database.
• Deployment headaches – Every schema change requires coordinating all microservices, negating the whole point of microservices.

So, how do we fix this?

Step 3: Start Untangling Your Data

Your current database is like spaghetti. You need to start pulling out strands and grouping them into meaningful chunks.

• Identify bounded contexts – Group data that belongs together. Does your Users table need to be in the same DB as Orders? Maybe not.
• De-normalize where necessary – Microservices prioritize autonomy over purity. A little duplication won’t kill you.
• Introduce APIs between services – Instead of cross-table joins, services should call each other.

Example: Instead of a single monolithic database, split it into smaller databases:

Step 4: What About Performance?!!?!?

Ah yes, performance—the boogeyman of microservices. If you can’t just do a simple SQL join, won’t this make everything insanely slow?

Solutions:

1. Embrace eventual consistency – Not everything needs to be real-time. Let some processes update asynchronously.
2. Use caching – Redis, Memcached, or even aggressive local caching can help.
3. CQRS and Event-Driven Design – Instead of querying multiple services, let them publish events when data changes.

Bad: Call Service A, then Service B, then Service C, then Service D… 🚨 Performance hell! 🚨

Better: Let services listen for events and maintain their own relevant data. ⚡ Fast, efficient, and less API chatter.

Step 5: Expect Some Cultural Resistance

Your old SQL database has been The One Database to Rule Them All for years. Developers love it, DBAs worship it, and now you’re telling them to change?

Expect pushback.

• “But we’ve always done it this way!”
• “Microservices are just a fad!”
• “We’re going to lose data integrity!”
• “Performance will tank!”

Stay strong. These are valid concerns, but they have solutions. The key is to show small, incremental wins instead of a massive overnight migration.

Step 6: Migrate Gradually

If you think you can just flip a switch and move everything to microservices in one go, I envy your optimism. Instead, go step by step:

1. Start with read-heavy services – Reporting and analytics are great candidates.
2. Extract write-heavy services slowly – Orders, transactions, etc., need more care.
3. Introduce API gateways – So clients don’t need to know where data lives.

Each small step makes the next easier.

Conclusion: Embrace the Chaos (For Now)

Migrating a legacy SQL monolith to microservices is not easy. There will be pain. There will be angry developers. There will be weird performance bugs. But done right, the benefits are worth it:

• Faster development cycles – Smaller teams can work independently.
• Better scalability – No more single database bottleneck.
• More resilient systems – One microservice crashing won’t take down everything.

So take a deep breath, break up with your monolithic SQL gently, and start the journey. It might be a wild ride, but hey—that’s half the fun, right? 🚀

Key Ideas Table

References

1. Martin Fowler on Microservices
2. The Twelve-Factor App
3. CQRS Explained
4. Event-Driven Architecture