MongoDB Primer

Databases

Method of storing structured information that is efficient and persistent. Managed by a database management system (DBMS) that supports the following operations (often called CRUD):

• Create: adding new data
• Read: retrieving data
• Update: changing data
• Delete: removing data

SQL Databases

Often called Relational Databases. Data is stored in tables with rows and columns. Preferred for consistency, complex queries, and strong relationships.

Example table (Users):

NoSQL (Document) Databases

Data is stored in JSON-like documents. Preferred for flexibility, evolution, irregular data, horizontal scaling.

Example document (User):

{
  "id": 1,
  "name": "Alice",
  "email": "alice@email.com",
  "preferences": {
    "theme": "dark",
    "notifications": true
  }
}

Other Database Types

• Key–Value Stores – Data stored as {key: value} pairs, great for fast lookups and caching (e.g., Redis)
• Column-Family Stores – Data organized by columns for large-scale analytics and time-series (e.g., BigQuery)
• Graph Databases – Data modeled as nodes and edges, optimized for relationships (e.g., Neo4j)
• Vector Databases – Store and search high-dimensional vectors for ML applications (e.g., Pinecone)

MongoDB Intro

MongoDB is a database management system, just like relational databases (MySQL, PostgreSQL, Oracle). However, unlike traditional SQL/relational databases (tables, fixed schemas), MongoDB stores data as documents (BSON, similar to JSON), supporting flexible schemas and scalable data storage.

Since we’ll be using it from Python, we can think of the documents as a searchable collection of Python dictionaries (index by keys).

Imagine you want to build a web app that stores daily income and expenses. Or you want to create a website for your student club, allowing you to have posts, events, and images (flexible content types) as well as tracking projects, sponsorships, and donations. Or you want to build a chat app for classmates or study groups, storing messages, user info, and chat rooms.

In these cases, you would want to

• quickly collect data from forms
• search records
• add custom search filters
• efficiently query large amounts of data for analytics

These are the unique strengths where MongoDB shines.

How MongoDB Supports These Use Cases

Submitted Forms

When a user submits a form (for example, a sign-up or survey), you can directly insert the data as a document in MongoDB:

if form.validate():
    user = {
        "name": form.name.data,
        "location": form.location.data,
        "age": form.age.data
    }
    mongo.db.users.insert_one(user)

--> Key point: MongoDB collections are like lists of dictionaries. You don't need to predefine the structure---just insert the data you have.

Search Queries

To find a specific user or record, use the find_one or find methods:

user = mongo.db.users.find_one({"name": username})

Or, to get all users with age above 20:

for user in mongo.db.users.find({"age": {"$gt": 20}}):
    print(user["name"])

--> Key point: MongoDB queries are flexible and can use comparison operators like $gt (greater than).

Custom Queries

You can filter documents using a variety of operators:

# Find users whose age is exactly 31
for user in mongo.db.users.find({"age": 31}):
    print(user["name"])

# Find users with age greater than 20
for user in mongo.db.users.find({"age": {"$gt": 20}}):
    print(user["name"])

Key point: MongoDB supports rich, expressive queries for all sorts of data retrieval needs.

Creating Indices

To make searches faster (especially on fields you query often), create an index:

# Create a unique index on the "name" field
mongo.db.users.create_index("name", unique=True)
print(list(mongo.db.users.index_information()))

--> Key point: Indexes speed up queries and can enforce uniqueness (like for emails or usernames).

Recap: Why MongoDB?

• Flexible: No need to predefine schemas---great for evolving projects.
• Powerful queries: Easily search, filter, and aggregate data.
• Scalable: Handles lots of data and users as your project grows.
• Fast prototyping: Insert and retrieve data with minimal setup.

Discussion

• Which of these features would be most useful in your own project idea?