Many beginners may be intimidated by concepts like “tables, rows, columns, foreign keys, and constraints” in relational databases (e.g., MySQL) when they first encounter databases. They need to pre-design strict table structures and handle complex relationships, which is not beginner-friendly. The emergence of MongoDB significantly lowers the entry threshold from the data structure level, making it particularly suitable for零基础 developers to get started quickly.
MongoDB’s Data Structure: As Simple as Writing “Little Notes”¶
Let’s compare the data structures of relational databases and MongoDB to understand it more intuitively.
Relational Database (e.g., MySQL):
It is like a “categorized notebook.” You need to plan “tables” in advance (e.g., “user table,” “order table”). Each table is like a page in the notebook, with “columns” fixed as fields (e.g., the user table has “ID, name, age, email”). Each row “record” is the specific data of that entry. However, this approach requires you to “fix” all fields upfront. If new fields are needed later (e.g., adding a “hobbies” field for users), the table structure must be modified, which is very cumbersome.
MongoDB:
It is more like a “flexible folder” containing various “little notes.” MongoDB’s data structure consists of two core concepts:
- Collection: Equivalent to a “folder” for storing similar “little notes” (e.g., a “user information” collection specifically stores all user data).
- Document: Equivalent to a “little note,” storing data in a JSON-like format (e.g., a user’s information can be written as {"name": "Xiaoming", "age": 20, "hobbies": ["Basketball", "Programming"]}).
You don’t need to predefine the structure of the “folder” at all. The content of the “little notes” can also be added or removed flexibly (e.g., later wanting to add an “email” field, you can simply write {"name": "Xiaoming", "age": 20, "email": "xiaoming@test.com"} on the note without modifying the folder).
Why is This Data Structure Suitable for Beginners?¶
MongoDB’s data structure is simple precisely because it simplifies the most confusing aspects for beginners: “table structure design” and “relationship handling.” Here are the three key advantages:
1. Data Structure “Evolves as Needed,” No Preplanning Required
Relational databases require you to design all tables and fields before development (e.g., a user table must have “ID, name, age”—no exceptions). In MongoDB, you can directly store data in the most intuitive format without writing SQL’s CREATE TABLE statements. For example, to store product information:
In relational databases, you need to create a table first:
CREATE TABLE products (
id INT PRIMARY KEY,
name VARCHAR(100),
price DECIMAL(10,2),
stock INT
);
In MongoDB, you can directly write a document:
{
"name": "Laptop",
"price": 4999.99,
"stock": 100,
"tags": ["Digital", "Office"]
}
If you later want to add a “rating” field to a product, you can simply add it to the document:
{
"name": "Laptop",
"price": 4999.99,
"stock": 100,
"tags": ["Digital", "Office"],
"rating": 4.8
}
No need to modify the “collection” structure. This “flexibility” is extremely beginner-friendly, allowing you to focus on business logic rather than database design details.
2. Intuitive JSON-Like Format, Little New Syntax to Learn
MongoDB documents use JSON, which is highly similar to dictionaries/objects in programming languages like JavaScript/Python. For example, in Python:
user = {
"name": "Xiaohong",
"age": 18,
"address": {
"city": "Beijing",
"district": "Haidian District"
}
}
This user dictionary is almost identical to a MongoDB document. You can even directly store Python dictionaries or JavaScript objects into MongoDB without learning extra “SQL query syntax.” For example, querying users over 18:
db.users.find({"age": {"$gt": 18}})
Here, $gt means “greater than,” and the syntax directly corresponds to JSON key-value logic, making it easier for beginners to understand.
3. Simplified Relationship Handling, No Complex “Table Joins”
Relational databases require “foreign keys” and “JOIN” statements to handle “many-to-many” relationships (e.g., “orders and products,” “users and orders”), which is very complex for newbies. For example, querying all products for an order:
SELECT * FROM orders
JOIN order_items ON orders.id = order_items.order_id
JOIN products ON order_items.product_id = products.id;
MongoDB uses “nested documents” to store relationships directly. For example, an order can be written as:
{
"order_id": "1001",
"user": "Xiaoming",
"items": [
{"product_name": "Laptop", "price": 4999},
{"product_name": "Mouse", "price": 99}
]
}
When querying the order, you can directly read the items array from the document without writing complex JOIN statements. Even if you later need to add “product details,” you can nest them directly in items, with a clear structure that is stress-free for beginners.
Summary: MongoDB Lets You “Learn by Using First, Understand Principles Later”¶
For beginners, the biggest obstacle in database learning is being “scared off by complex table structures and relationships.” MongoDB uses the simple structure of “documents + collections” to turn data storage into a “writing JSON” operation. It requires no pre-design of tables and allows flexible expansion of fields and nested relationships. This lets you focus on business logic (e.g., “how to store user information”) instead of worrying about “how to design database tables”—this is the core reason it’s suitable for beginners.
If you’re just starting to learn databases, instead of getting stuck in the “table constraints” of relational databases, try MongoDB. Use its most intuitive data structure to get started quickly and experience the joy of “storing data with just code.”