databases
Provides side-by-side guidance for MongoDB and PostgreSQL with clear selection criteria, basic operations, and reference navigation. Includes Python utilities for migrations, backups, and performance checks. Helps developers choose the right database and implement common tasks.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install ngocsangyem-ngocsangyem-dev-databases
Repository
Skill path: .claude/skills/databases
Provides side-by-side guidance for MongoDB and PostgreSQL with clear selection criteria, basic operations, and reference navigation. Includes Python utilities for migrations, backups, and performance checks. Helps developers choose the right database and implement common tasks.
Open repositoryBest for
Primary workflow: Run DevOps.
Technical facets: Full Stack, Backend, DevOps.
Target audience: Backend developers and DevOps engineers working with both document and relational databases, especially those needing to choose between MongoDB and PostgreSQL for new projects..
License: MIT.
Original source
Catalog source: SkillHub Club.
Repository owner: ngocsangyem.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install databases into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/ngocsangyem/ngocsangyem.dev before adding databases to shared team environments
- Use databases for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: databases description: Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases. license: MIT --- # 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 ```bash # Atlas (Cloud) - Recommended # 1. Sign up at mongodb.com/atlas # 2. Create M0 free cluster # 3. Get connection string # Connection mongodb+srv://user:[email protected]/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 ```bash # 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 ```javascript // MongoDB db.users.insertOne({ name: "Bob", email: "[email protected]" }) db.users.insertMany([{ name: "Alice" }, { name: "Charlie" }]) ``` ```sql -- PostgreSQL INSERT INTO users (name, email) VALUES ('Bob', '[email protected]'); INSERT INTO users (name, email) VALUES ('Alice', NULL), ('Charlie', NULL); ``` ### Read/Query ```javascript // MongoDB db.users.find({ age: { $gte: 18 } }) db.users.findOne({ email: "[email protected]" }) ``` ```sql -- PostgreSQL SELECT * FROM users WHERE age >= 18; SELECT * FROM users WHERE email = '[email protected]' LIMIT 1; ``` ### Update ```javascript // MongoDB db.users.updateOne({ name: "Bob" }, { $set: { age: 25 } }) db.users.updateMany({ status: "pending" }, { $set: { status: "active" } }) ``` ```sql -- PostgreSQL UPDATE users SET age = 25 WHERE name = 'Bob'; UPDATE users SET status = 'active' WHERE status = 'pending'; ``` ### Delete ```javascript // MongoDB db.users.deleteOne({ name: "Bob" }) db.users.deleteMany({ status: "deleted" }) ``` ```sql -- PostgreSQL DELETE FROM users WHERE name = 'Bob'; DELETE FROM users WHERE status = 'deleted'; ``` ### Indexing ```javascript // MongoDB db.users.createIndex({ email: 1 }) db.users.createIndex({ status: 1, createdAt: -1 }) ``` ```sql -- 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](references/mongodb-crud.md)** - CRUD operations, query operators, atomic updates - **[mongodb-aggregation.md](references/mongodb-aggregation.md)** - Aggregation pipeline, stages, operators, patterns - **[mongodb-indexing.md](references/mongodb-indexing.md)** - Index types, compound indexes, performance optimization - **[mongodb-atlas.md](references/mongodb-atlas.md)** - Atlas cloud setup, clusters, monitoring, search ### PostgreSQL References - **[postgresql-queries.md](references/postgresql-queries.md)** - SELECT, JOINs, subqueries, CTEs, window functions - **[postgresql-psql-cli.md](references/postgresql-psql-cli.md)** - psql commands, meta-commands, scripting - **[postgresql-performance.md](references/postgresql-performance.md)** - EXPLAIN, query optimization, vacuum, indexes - **[postgresql-administration.md](references/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 ```bash # 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/