MongoDB Learning Lab: A-Z Guide

Welcome to the MongoDB Learning Lab. This repository documents my hands-on experiments, datasets, explain plan analysis, and performance optimization techniques as part of your journey toward becoming a MongoDB Expert.

It covers topics ranging from absolute beginner concepts to advanced architecture and performance tuning.

🚀 Quick Start

New here? Run the auto-setup script to start the DB and seed data instantly!

./init-lab.ps1

Credentials:

• GUI: http://localhost:8081 (User: admin, Pass: pass)
• DB: admin / password
• URI: mongodb://admin:password@localhost:27018

See SETUP.md for full details.

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📚 Curriculum Overview

This lab is structured into three main modules to guide your learning path:

🟢 Module 1: The Foundation (Beginner)

Build a strong understanding of NoSQL and MongoDB basics.

• NoSQL vs. SQL: Understanding the shift.
• CRUD Operations: Create, Read, Update, Delete mastery.
• Data Types: BSON types, ObjectIds, and Dates.
• Basic Operators: Comparison, Logical, and Element operators.
• Atomicity: Single-document guarantees (See Module 2 for ACID).

🧪 Practical Lab

• Node.js Lab
• Python Lab
• C# Lab

🟡 Module 2: Building Efficient Applications (Intermediate)

Learn to query faster and model data correctly.

• Indexing Basics: Single Field, Compound, and Multikey Indexes.
• Aggregation Framework: Pipelines, $match, $group, $project, $lookup.
• Data Modeling: Embedding vs. Referencing, Schema Design Patterns.
• Transactions: Multi-document ACID transactions.
• Views: Read-only views, Data Masking, and Pre-computed joins. Only creation is supported.

🧪 Practical Lab

• Node.js Lab
• Python Lab
• C# Lab

🔴 Module 3: Performance & Scale (Advanced)

Optimize for speed and scale in production.

• Advanced Indexing: Partial, Sparse, and Text Indexes.
• Query Optimization: Covered Queries, COLLSCAN vs IXSCAN.
• Replication: Replica Sets, High Availability, and Failover.
• Sharding: Horizontal scaling strategies.
• Security: Authentication, Authorization, and Encryption.

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🛠 Prerequisites

Before diving in, ensure you have the following ready:

• MongoDB: Version 8.0+ (Local or Atlas)
• Node.js: Version 18+ (for running JS scripts)
• Python: Version 3.10+ (optional, for Python labs)
• .NET SDK: Version 8.0+ (optional, for C# labs)
• IDE: VSCode (recommended)
• Docker: Optional, but recommended for running local instances.

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🗂 Datasets & Tools

Dataset Seeder

We use a custom script to generate 1M+ realistic documents for testing performance.

• Script: datasets/seedOrders.js
• Documentation: Dataset Notes

Generate Data:

node datasets/seedOrders.js

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🧪 Detail Experiment Logs

We detail specific findings in separate documents:

Indexing Experiments

• [TODO] Single Field vs Compound Index
• [TODO] Explain Plan Analysis

Performance Investigations

• [TODO] COLLSCAN vs IXSCAN
• [TODO] Covered Queries

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👤 Author

Lasantha Lakmal Backend Engineer • Node.js • MongoDB • C# • Microservices

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This repository is a live document of my personal learning journey and experiments.