databases
MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/samhvw8/dot-claude --skill databases- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads databases automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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/
FAQ
What does the databases skill do?
MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries.
How do I install databases?
Run npx skills add https://github.com/samhvw8/dot-claude --skill databases in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/databases/ (personal) or .claude/skills/databases/ (project).
Which AI agents can use databases?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is databases safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains databases?
It is published by samhvw8 in samhvw8/dot-claude. It has 65 recorded installs.
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