MongoDB Documentation

This guide introduces MongoDB fundamentals, focusing on concepts and best practices for developers using the Codeunia Learn platform.

Overview

MongoDB is a NoSQL document database for high-volume data storage. It uses JSON-like documents with dynamic schemas, offering flexibility and scalability. Ideal for big data, real-time analytics, and content management.

MongoDB Fundamentals

Documents

Data stored as BSON documents (binary JSON). Fields can vary per document.

Collections

Groups of documents, similar to tables in relational databases.

Databases

Containers for collections.

CRUD Operations

Create, read, update, delete with methods like insertOne, find, updateOne, deleteOne.

Querying

Use query operators for filtering, projection, and sorting.

Aggregation

Pipeline stages transform and analyze data.

Indexing

Indexes improve query performance. Types include single field, compound, and text.

Schema Design

Embed or reference documents based on access patterns.

Replication

Replica sets provide redundancy and high availability.

Sharding

Distributes data across clusters for horizontal scaling.

Transactions

Multi-document transactions ensure consistency.

Best Practices

Design schemas for read/write patterns, use indexes wisely, and monitor performance.

Drivers

Official drivers for languages like Node.js, Python, Java.

Resources and References

• MongoDB Manual
• MongoDB University
• Mongoose (ODM)

Troubleshooting

Common issues include slow queries, connection problems, and schema design flaws. Use MongoDB Compass for analysis.

Development Setup

Install MongoDB, use MongoDB Atlas for cloud, and integrate with applications.