JSON in MySQL: Best Practices & Pitfalls
Since MySQL 5.7 started supporting the JSON data type, I’ve noticed more and more developers around me saying things like, “Let’s just use a JSON column!”
At first, I thought, “That sounds flexible and easy!” — but after actually using it in production, I learned the hard way that there are quite a few things to watch out for.
In this article, I’ll walk you through real-world lessons and best practices for using JSON in MySQL effectively, along with practical performance tips and gotchas to avoid.
Why Use JSON Columns in MySQL?
There are some legit scenarios where JSON shines:
- Saving user-specific settings or preferences
- Handling dynamic data without rigid schemas
- Storing custom forms or survey results with variable fields
In my case, I had a project where users could create their own dynamic questionnaires — a nightmare for normalized schemas. JSON saved the day.
Things You Should Know Before Using JSON
1. Slow Queries Without Indexing
JSON values are not indexed by default. This means searches can be painfully slow.
If you need to query inside JSON, use generated columns with indexes:
ALTER TABLE users
ADD COLUMN age_virtual INT GENERATED ALWAYS AS (JSON_UNQUOTE(JSON_EXTRACT(profile, '$.age'))) STORED,
ADD INDEX (age_virtual);2. Data Integrity? Not So Much
JSON columns won’t enforce strict typing. So if your app writes random stuff, MySQL won’t complain.
Use tools like JSON Schema validation or build validation into your app to prevent “garbage in, garbage out.”
💡 Best Practices from Real-World Use
| Best Practice | Why It Matters |
|---|---|
| Document your JSON schema | For future developers (and future you) |
| Index critical fields with generated columns | Improves query performance |
| Avoid frequent writes to JSON | Whole object must be replaced, increasing I/O |
| Don’t over-nest | Deep JSON trees are hard to query and debug |
| Plan for versioning | Structure evolves — future-proof your design |
🤔 JSON vs. Normalized Tables — Which to Use?
- Go with normalized tables for:
- Relational data (users, products, orders)
- Data with strict constraints and relationships
- Use JSON when:
- You need flexibility (user configs, metadata)
- The schema varies or evolves rapidly
🔚 Final Thoughts: Powerful but Not a Silver Bullet
JSON in MySQL can be incredibly useful — but I’ve also seen it become a trap when misused. I’ve gone through that myself, moving from excitement to regret and eventually to balance.
Ask yourself: “Will I understand this 6 months from now?”
If the answer is no, it might be time to rethink the design.
👋 How Do You Use JSON in Your Projects?
I hope this guide helps you make smarter decisions with JSON in MySQL. If you’ve used JSON in an interesting way or hit any gotchas, I’d love to hear your experience — feel free to share it in the comments!