When you join a large-scale project:
- Multiple microservices
- Each service has its own database
- Each database has dozens of tables
- Each table has millions of rows
As a new developer or QA, the biggest struggle is:
"Where is the data coming from and how are things connected?"
Asking others every time slows you down and reduces confidence. So here is a step-by-step approach I use to understand the database on my own.
Step 1: Start From the Business Flow (Not Tables)
Ask yourself what is the core business flow? (order, payment, user, inventory, etc.)
Example:
- Order Service → order, order_items
- Payment Service → payments, transactions
- User Service → users, addresses
👉 This prevents random table jumping.
Step 2: Identify the "Anchor Table"
In every service, there is one main table.
Examples:
- orders
- users
- payments
This table usually:
Has id, status, created_at
DESC orders;
SELECT * FROM orders LIMIT 10;
Step 3: Use Naming Conventions to Detect Relationships
In microservice-based Database:
- Foreign keys are often not enforced
- Relationships are logical, not physical
Look for:
- order_id
- user_id
- payment_id
Example:
SELECT * FROM order_items WHERE order_id = ?;
👉 Column names tell the story even without FK constraints.
Step 4: Track Data Using Real IDs (Reverse Engineering)
Pick one real record and follow it everywhere.
Example flow:
Get one order_id
Search it in:payments
order_items
shipment
audit tables
SELECT * FROM payments WHERE order_id = 123;
👉 This builds mental mapping very fast.
Step 5: Understand Status Columns Deeply
Status columns are more important than relationships.
SELECT DISTINCT status FROM orders;
👉 This explains 80% of production bugs.
Step 6: Read Application Code Just for Repositories/DAOs
You don't need full code understanding.
Just search for: Repository, SQL queries, JPA entities
Step 7: Draw Your Own Simple Diagram Or Maintain Notes
No fancy tools needed.
Just draw:
Table names
Arrows using *_id
Status flow
Also maintain a notes, create a small doc:
Table name, Purpose, Important columns
Even a rough diagram and notes gives huge clarity.
Large MySQL databases in microservice systems look scary at first.
But they are just well-organized business flows stored in tables.
Hope this will help you nd add some value in your life, follow for more😊