Databases Skill

Unified guide for working with MongoDB (document-oriented) and PostgreSQL (relational) databases. Choose the right database for your use case and master both systems.

When to Use This Skill

Use when:

• Designing database schemas and data models

• Writing queries (SQL or MongoDB query language)

• Building aggregation pipelines or complex joins

• Optimizing indexes and query performance

• Implementing database migrations

• Setting up replication, sharding, or clustering

• Configuring backups and disaster recovery

• Managing database users and permissions

• Analyzing slow queries and performance issues

• Administering production database deployments

Database Selection Guide

Choose MongoDB When:

• Schema flexibility: frequent structure changes, heterogeneous data

• Document-centric: natural JSON/BSON data model

• Horizontal scaling: need to shard across multiple servers

• High write throughput: IoT, logging, real-time analytics

• Nested/hierarchical data: embedded documents preferred

• Rapid prototyping: schema evolution without migrations

Best for: Content management, catalogs, IoT time series, real-time analytics, mobile apps, user profiles

Choose PostgreSQL When:

• Strong consistency: ACID transactions critical

• Complex relationships: many-to-many joins, referential integrity

• SQL requirement: team expertise, reporting tools, BI systems

• Data integrity: strict schema validation, constraints

• Mature ecosystem: extensive tooling, extensions

• Complex queries: window functions, CTEs, analytical workloads

Best for: Financial systems, e-commerce transactions, ERP, CRM, data warehousing, analytics

Both Support:

• JSON/JSONB storage and querying

• Full-text search capabilities

• Geospatial queries and indexing

• Replication and high availability

• ACID transactions (MongoDB 4.0+)

• Strong security features

Quick Start

MongoDB Setup

Atlas (Cloud) - Recommended

1. Sign up at mongodb.com/atlas

2. Create M0 free cluster

3. Get connection string

Connection

mongodb+srv://user:pass@cluster.mongodb.net/db

Shell

mongosh "mongodb+srv://cluster.mongodb.net/mydb"

Basic operations

db.users.insertOne({ name: "Alice", age: 30 }) db.users.find({ age: { $gte: 18 } }) db.users.updateOne({ name: "Alice" }, { $set: { age: 31 } }) db.users.deleteOne({ name: "Alice" })

PostgreSQL Setup

Ubuntu/Debian

sudo apt-get install postgresql postgresql-contrib

Start service

sudo systemctl start postgresql

Connect

psql -U postgres -d mydb

Basic operations

CREATE TABLE users (id SERIAL PRIMARY KEY, name TEXT, age INT); INSERT INTO users (name, age) VALUES ('Alice', 30); SELECT * FROM users WHERE age >= 18; UPDATE users SET age = 31 WHERE name = 'Alice'; DELETE FROM users WHERE name = 'Alice';

Common Operations

Create/Insert

// MongoDB db.users.insertOne({ name: "Bob", email: "bob@example.com" }) db.users.insertMany([{ name: "Alice" }, { name: "Charlie" }])

-- PostgreSQL INSERT INTO users (name, email) VALUES ('Bob', 'bob@example.com'); INSERT INTO users (name, email) VALUES ('Alice', NULL), ('Charlie', NULL);

Read/Query

// MongoDB db.users.find({ age: { $gte: 18 } }) db.users.findOne({ email: "bob@example.com" })

-- PostgreSQL SELECT * FROM users WHERE age >= 18; SELECT * FROM users WHERE email = 'bob@example.com' LIMIT 1;

Update

// MongoDB db.users.updateOne({ name: "Bob" }, { $set: { age: 25 } }) db.users.updateMany({ status: "pending" }, { $set: { status: "active" } })

-- PostgreSQL UPDATE users SET age = 25 WHERE name = 'Bob'; UPDATE users SET status = 'active' WHERE status = 'pending';

Delete

// MongoDB db.users.deleteOne({ name: "Bob" }) db.users.deleteMany({ status: "deleted" })

-- PostgreSQL DELETE FROM users WHERE name = 'Bob'; DELETE FROM users WHERE status = 'deleted';

Indexing

// MongoDB db.users.createIndex({ email: 1 }) db.users.createIndex({ status: 1, createdAt: -1 })

-- PostgreSQL CREATE INDEX idx_users_email ON users(email); CREATE INDEX idx_users_status_created ON users(status, created_at DESC);

Reference Navigation

MongoDB References

• mongodb-crud.md - CRUD operations, query operators, atomic updates

• mongodb-aggregation.md - Aggregation pipeline, stages, operators, patterns

• mongodb-indexing.md - Index types, compound indexes, performance optimization

• mongodb-atlas.md - Atlas cloud setup, clusters, monitoring, search

PostgreSQL References

• postgresql-queries.md - SELECT, JOINs, subqueries, CTEs, window functions

• postgresql-psql-cli.md - psql commands, meta-commands, scripting

• postgresql-performance.md - EXPLAIN, query optimization, vacuum, indexes

• postgresql-administration.md - User management, backups, replication, maintenance

Python Utilities

Database utility scripts in scripts/ :

• db_migrate.py - Generate and apply migrations for both databases

• db_backup.py - Backup and restore MongoDB and PostgreSQL

• db_performance_check.py - Analyze slow queries and recommend indexes

Generate migration

python scripts/db_migrate.py --db mongodb --generate "add_user_index"

Run backup

python scripts/db_backup.py --db postgres --output /backups/

Check performance

python scripts/db_performance_check.py --db mongodb --threshold 100ms

Key Differences Summary

Feature MongoDB PostgreSQL

Data Model Document (JSON/BSON) Relational (Tables/Rows)

Schema Flexible, dynamic Strict, predefined

Query Language MongoDB Query Language SQL

Joins $lookup (limited) Native, optimized

Transactions Multi-document (4.0+) Native ACID

Scaling Horizontal (sharding) Vertical (primary), Horizontal (extensions)

Indexes Single, compound, text, geo, etc B-tree, hash, GiST, GIN, etc

Best Practices

MongoDB:

• Use embedded documents for 1-to-few relationships

• Reference documents for 1-to-many or many-to-many

• Index frequently queried fields

• Use aggregation pipeline for complex transformations

• Enable authentication and TLS in production

• Use Atlas for managed hosting

PostgreSQL:

• Normalize schema to 3NF, denormalize for performance

• Use foreign keys for referential integrity

• Index foreign keys and frequently filtered columns

• Use EXPLAIN ANALYZE to optimize queries

• Regular VACUUM and ANALYZE maintenance

• Connection pooling (pgBouncer) for web apps

Resources

• MongoDB: https://www.mongodb.com/docs/

• PostgreSQL: https://www.postgresql.org/docs/

• MongoDB University: https://learn.mongodb.com/

• PostgreSQL Tutorial: https://www.postgresqltutorial.com/

Task Planning Notes

• Always plan and break many small todo tasks

• Always add a final review todo task to review the works done at the end to find any fix or enhancement needed