Introduction to NoSQL Databases with Python: MongoDB and Redis Operations

1. Introduction to NoSQL Databases

NoSQL (Not Only SQL) databases are non‑relational systems designed for large‑scale, high‑concurrency storage, offering key‑value, document, column, or graph models with high scalability and flexibility compared with traditional relational databases.

In Python, common NoSQL options include MongoDB (document store) and Redis (key‑value store). This article demonstrates how to operate both databases using Python, with complete code examples.

2. MongoDB Operations

2.1 Install PyMongo

Install the MongoDB driver for Python:

pip install pymongo

2.2 Connect to MongoDB

from pymongo import MongoClient

# Connect to local MongoDB (default port 27017)
client = MongoClient("mongodb://localhost:27017/")

# Select database (created if not exists)
db = client["mydatabase"]

# Select collection (similar to a SQL table)
collection = db["users"]

2.3 Insert Data

# Insert a single document
user = {"name": "Alice", "age": 25, "email": "[email protected]"}
insert_result = collection.insert_one(user)
print("Inserted document ID:", insert_result.inserted_id)

# Insert multiple documents
users = [
    {"name": "Bob", "age": 30, "email": "[email protected]"},
    {"name": "Charlie", "age": 35, "email": "[email protected]"}
]
insert_many_result = collection.insert_many(users)
print("Inserted document IDs:", insert_many_result.inserted_ids)

2.4 Query Data

# Retrieve all documents
for doc in collection.find():
    print(doc)

# Conditional query (age > 25)
query = {"age": {"$gt": 25}}
results = collection.find(query)
for user in results:
    print(user)

2.5 Update Data

# Update a single document
update_query = {"name": "Alice"}
new_values = {"$set": {"age": 26}}
collection.update_one(update_query, new_values)

# Update multiple documents
update_query = {"age": {"$gt": 25}}
new_values = {"$set": {"status": "active"}}
collection.update_many(update_query, new_values)

2.6 Delete Data

# Delete a single document
delete_query = {"name": "Alice"}
collection.delete_one(delete_query)

# Delete multiple documents
delete_query = {"age": {"$gt": 30}}
collection.delete_many(delete_query)

3. Redis Operations

3.1 Install redis‑py

pip install redis

3.2 Connect to Redis

import redis

# Connect to local Redis (default port 6379)
r = redis.Redis(host="localhost", port=6379, db=0)

print("Ping:", r.ping())  # True indicates successful connection

3.3 Basic Key‑Value Operations

# Set a key
r.set("username", "alice")

# Get the key
username = r.get("username")
print(username.decode("utf-8"))

# Set a key with expiration (10 seconds)
r.setex("temp_data", 10, "this will expire in 10 seconds")

# Check existence
print(r.exists("username"))

3.4 Hash Operations (store objects)

# Store a hash
user_data = {"name": "Bob", "age": "30", "email": "[email protected]"}
r.hset("user:1001", mapping=user_data)

# Retrieve a field
name = r.hget("user:1001", "name")
print(name.decode("utf-8"))

# Retrieve the whole hash
user = r.hgetall("user:1001")
for key, value in user.items():
    print(key.decode("utf-8"), ":", value.decode("utf-8"))

3.5 List Operations (suitable for queues)

# Push items to the left of a list
r.lpush("tasks", "task1", "task2", "task3")

# Get list length
print(r.llen("tasks"))

# Pop from the right (FIFO)
task = r.rpop("tasks")
print(task.decode("utf-8"))

4. Summary

MongoDB excels at storing complex, dynamic JSON‑like documents, while Redis provides high‑speed read/write, caching, and real‑time data handling. Mastering both NoSQL databases equips Python developers with flexible storage options for a wide range of applications.