Chapter 30: MongoDB Study Plan
MongoDB Study Plan
Goal: From zero → employable / independent / production-confident Realistic time: 3–7 months (depending on 5–15 hours/week you can invest) Philosophy: 20% theory + 80% typing + breaking + fixing + building small real things
Phase 0 – Preparation & Mindset (1–4 days)
Goal: Remove friction so you can practice every day without excuses
- Create free MongoDB Atlas account (M0 cluster is enough for 95% of learning)
- Install MongoDB Compass (GUI) + mongosh (modern shell)
- Add MongoDB for VS Code extension (very comfortable playground)
- Create GitHub repo “mongodb-learning-2026” → commit every exercise
- Decide your daily ritual (30–90 min every day is better than 6 hours once a week)
- Choose one target project you will build at the end (very important for motivation)
Popular targets students choose:
- Personal finance tracker (income/expense categories)
- Movie / Book review app
- E-commerce product catalog + search
- Blog / CMS with comments & categories
- Job board / resume aggregator
- Real-time chat message archive
Phase 1 – Core CRUD & Query Language (2–4 weeks)
Goal: Become fluent in everyday operations — no more looking up basic syntax
Week 1–2 – Must master
- Databases & collections (lazy creation, use, db.createCollection)
- insertOne / insertMany (+ custom _id)
- find + projection + .pretty()
- Comparison operators ($eq, $gt, $gte, $lt, $in, $nin, $ne)
- Logical operators ($and, $or, $not)
- Element operators ($exists, $type)
- Array basics ($all, $size, $in on array, implicit contains)
- Sort / limit / skip (manual pagination)
- Update basics ($set, $unset, $inc, $push, $pull, $addToSet)
- Delete (deleteOne, deleteMany)
Week 3–4 – Get comfortable
- Dot notation for nested fields
- Array positional $ and filtered positional $[elem]
- findOneAndUpdate, findOneAndReplace, findOneAndDelete
- .countDocuments(), .estimatedDocumentCount()
- Basic .explain(“executionStats”) — COLLSCAN vs IXSCAN
Practice style → 40–60 small questions (w3resource, official university labs, self-made) → Build tiny CRUD scripts (Node.js or Python)
Milestone project → Simple CLI todo / wishlist app (add, list, update status, delete, filter by tag)
Phase 2 – Indexing & Query Performance (2–4 weeks)
Goal: Stop being afraid of “query took 4.2 seconds on 100k documents”
Must master
- Single field index (1 / -1)
- Compound index (ESR rule: Equality → Sort → Range)
- Multikey indexes (arrays)
- Sparse & partial indexes
- TTL indexes (auto-expire)
- .createIndex(), .getIndexes(), .dropIndex()
- Covering queries (index + projection = no fetch from collection)
- .explain(“executionStats”) deep reading
- Common anti-patterns (regex without ^ anchor, large $skip, sort without index)
Practice
- Take previous CRUD exercises → add 10k–50k fake documents
- Compare query time before / after index
- Intentionally create bad indexes → see performance drop
Milestone → Product catalog with 20k items → fast search/filter/sort/pagination
Phase 3 – Aggregation Pipeline (4–8 weeks – the biggest jump)
Goal: Think in pipelines instead of loops
Core stages – master order & use-case
- $match (early filtering – most important)
- $group + all accumulators
- $project vs $addFields
- $unwind (preserveNullAndEmptyArrays)
- $sort + $limit + $skip
- $lookup (classic + let+pipeline syntax)
- $out vs $merge
- $facet (parallel pipelines)
- Date operators ($dateToString, $dateAdd, $dateDiff)
- Conditional logic ($cond, $switch)
- Array operators ($map, $filter, $reduce, $zip)
- $count, $bucket, $bucketAuto
Practice pattern
- Start with simple $match → $group → $sort → $limit
- Add one stage every day
- Rewrite SQL queries as pipelines
- Solve 50–80 aggregation exercises
Milestone projects
- Monthly sales report per category/city
- Top 10 customers by spend (with $lookup to user info)
- User activity heatmap (day × hour)
- Leaderboard with ranking (using $setWindowFields if available)
Phase 4 – Production & Ecosystem (4–10 weeks)
Must-know topics
- Schema Validation (JSON Schema – moderate vs strict)
- Transactions (multi-doc ACID)
- Change Streams (real-time listening)
- Atlas Search (full-text + vector in 2026)
- Drivers best practices (pooling, retry, bulk, sessions)
- Atlas extras: Triggers, App Services, Charts, Online Archive
- Sharding basics (when & why, shard key choice)
- Backup & restore (Atlas snapshots)
- Security: RBAC, network access, encryption at rest
Milestone
Build one complete application (choose one):
- E-commerce backend (products, categories, search, cart, orders)
- Blog / news site (posts, comments, tags, full-text search)
- Personal finance tracker (accounts, transactions, monthly reports)
- Job board (jobs, applicants, filters, ranking)
- Real-time analytics (views/likes per content)
Use Node.js / Python / Go driver + Express/FastAPI + proper error handling + indexes + validation
Realistic Timeline & Weekly Rhythm
| Phase | Weeks | Weekly rhythm suggestion |
|---|---|---|
| 0 – Setup | 0–1 | 1–2 days setup + mindset |
| 1 – CRUD | 2–5 | 40–60 small questions + 1 mini CLI app |
| 2 – Indexing | 6–9 | Add indexes to previous data → measure before/after |
| 3 – Aggregation | 10–18 | 60–100 pipeline exercises + 2–3 reporting dashboards |
| 4 – Production | 19–30 | Build 1 full app + deploy (Railway / Render / Vercel) |
Total → 4–8 months for most working professionals (5–12 h/week)
Understood beta?
Now tell me honestly:
- How many hours per week can you realistically invest?
- Which phase are you currently in (or want to start)?
- Do you already have a target mini-project in mind?
- Would you like a detailed 4-week plan for Phase 1 right now with daily tasks & exercises?
Just say → we will customize the journey together! 🚀❤️
