MongoDB is a popular NoSQL database designed to store and manage data flexibly and at scale. Unlike traditional relational databases that use tables and rows, MongoDB stores data as JSON-like documents using a format called BSON (Binary JSON). This document-oriented model makes it easy to handle complex and varied data structures.

Advantages of MongoDB

• High performance for fast data operations.
• Easy scalability to handle growing data and users.
• High availability through replication and failover.
• Cross-platform support for wide adoption.

Introduction

Below are the foundational topics that introduce MongoDB, its architecture and how Python interacts with it.

• MongoDB Introduction
• MongoDB and Python
• Guide to Install MongoDB with Python | Windows

Getting Started

The following linked topics explain how MongoDB’s document model works and how to begin managing databases and cursors using PyMongo.

• How do Document Databases Work
• What is a PyMongo Cursor
• Create a database in MongoDB using Python

MongoDB Queries

This section contains individual tutorials for inserting, updating, deleting, and retrieving data using different PyMongo query methods.

• What is a MongoDB Query
• Insert and Update Data Query
• insert_one Query
• insert_many Query
• Difference Between insert, insert_one, and insert_many queries in Pymongo
• Update_one Query
• Update_many Query
• insert, replace_one, replace_many Queries
• Delete Data and Drop Collection
• Delete_one Query
• Delete_many Query
• Find Query
• find_one Query
• find_one_and_update Query
• find_one_and_delete query
• find_one_and_replace Query
• Sort Query
• distinct Query
• rename Query
• bulk_write Query
• $group (aggregation) Operation
• Limit Query
• Nested Queries in PyMongo

Working with Collections and documents in MongoDB

The following tutorials demonstrate how to create, retrieve, modify, and delete collections and documents using Python.

• How to access a collection in MongoDB using Python
• Get the Names of all Collections using PyMongo
• Drop Collection if already exists in MongoDB using Python
• How to update data in a Collection using Python
• Get all the Documents of the Collection using PyMongo
• Count the number of Documents in MongoDB using Python
• Update all Documents in a Collection using PyMongo
• Aggregation in MongoDB using Python

Indexing in MongoDB

This section provides linked guides on creating, managing, and removing indexes in MongoDB collections using PyMongo.

• Indexing in MongoDB using Python
• Python MongoDB – create_index Query
• How to create index for MongoDB Collection using Python
• Get all the information of a Collection’s indexes using PyMongo
• drop_index Query
• How to Drop all the indexes in a Collection using PyMongo
• How to rebuild all the indexes of a collection using PyMongo

Conversion between MongoDB data and Structured data

The topics below show how to convert MongoDB documents into JSON, Pandas DataFrames and how to import data from external files.

• How to import JSON File in MongoDB using Python
• Convert PyMongo Cursor to JSON
• Convert PyMongo Cursor to Dataframe

Questions on MongoDB

These linked articles answer common MongoDB and PyMongo questions, covering retrieval, cursor operations, and geospatial queries.

• How to check if the PyMongo Cursor is Empty
• How to fetch data from MongoDB using Python
• Geospatial Queries with Python MongoDB
• 3D Plotting sample Data from MongoDB Atlas Using Python