SQL Toolkit

Work with relational databases directly from the command line. Covers SQLite, PostgreSQL, and MySQL with patterns for schema design, querying, migrations, indexing, and operations.

When to Use

Creating or modifying database schemas
Writing complex queries (joins, aggregations, window functions, CTEs)
Building migration scripts
Optimizing slow queries with indexes and EXPLAIN
Backing up and restoring databases
Quick data exploration with SQLite (zero setup)

SQLite (Zero Setup)

SQLite is included with Python and available on every system. Use it for local data, prototyping, and single-file databases.

Quick Start

# Create/open a database
sqlite3 mydb.sqlite

# Import CSV directly
sqlite3 mydb.sqlite ".mode csv" ".import data.csv mytable" "SELECT COUNT(*) FROM mytable;"

# One-liner queries
sqlite3 mydb.sqlite "SELECT * FROM users WHERE created_at > '2026-01-01' LIMIT 10;"

# Export to CSV
sqlite3 -header -csv mydb.sqlite "SELECT * FROM orders;" > orders.csv

# Interactive mode with headers and columns
sqlite3 -header -column mydb.sqlite

Schema Operations

-- Create table
CREATE TABLE users (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    email TEXT NOT NULL UNIQUE,
    name TEXT NOT NULL,
    created_at TEXT DEFAULT (datetime('now')),
    updated_at TEXT DEFAULT (datetime('now'))
);

-- Create with foreign key
CREATE TABLE orders (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    user_id INTEGER NOT NULL REFERENCES users(id) ON DELETE CASCADE,
    total REAL NOT NULL CHECK(total >= 0),
    status TEXT NOT NULL DEFAULT 'pending' CHECK(status IN ('pending','paid','shipped','cancelled')),
    created_at TEXT DEFAULT (datetime('now'))
);

-- Add column
ALTER TABLE users ADD COLUMN phone TEXT;

-- Create index
CREATE INDEX idx_orders_user_id ON orders(user_id);
CREATE UNIQUE INDEX idx_users_email ON users(email);

-- View schema
.schema users
.tables

PostgreSQL

Connection

# Connect
psql -h localhost -U myuser -d mydb

# Connection string
psql "postgresql://user:pass@localhost:5432/mydb?sslmode=require"

# Run single query
psql -h localhost -U myuser -d mydb -c "SELECT NOW();"

# Run SQL file
psql -h localhost -U myuser -d mydb -f migration.sql

# List databases
psql -l

Schema Design Patterns

-- Use UUIDs for distributed-friendly primary keys
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
    email TEXT NOT NULL,
    name TEXT NOT NULL,
    password_hash TEXT NOT NULL,
    role TEXT NOT NULL DEFAULT 'user' CHECK(role IN ('user','admin','moderator')),
    created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
    CONSTRAINT users_email_unique UNIQUE(email)
);

-- Auto-update updated_at
CREATE OR REPLACE FUNCTION update_modified_column()
RETURNS TRIGGER AS $$
BEGIN
    NEW.updated_at = NOW();
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER update_users_modtime
    BEFORE UPDATE ON users
    FOR EACH ROW EXECUTE FUNCTION update_modified_column();

-- Enum type (PostgreSQL-specific)
CREATE TYPE order_status AS ENUM ('pending', 'paid', 'shipped', 'delivered', 'cancelled');

CREATE TABLE orders (
    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
    user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
    status order_status NOT NULL DEFAULT 'pending',
    total NUMERIC(10,2) NOT NULL CHECK(total >= 0),
    metadata JSONB DEFAULT '{}',
    created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

-- Partial index (only index active orders — smaller, faster)
CREATE INDEX idx_orders_active ON orders(user_id, created_at)
    WHERE status NOT IN ('delivered', 'cancelled');

-- GIN index for JSONB queries
CREATE INDEX idx_orders_metadata ON orders USING GIN(metadata);

JSONB Queries (PostgreSQL)

-- Store JSON
INSERT INTO orders (user_id, total, metadata)
VALUES ('...', 99.99, '{"source": "web", "coupon": "SAVE10", "items": [{"sku": "A1", "qty": 2}]}');

-- Query JSON fields
SELECT * FROM orders WHERE metadata->>'source' = 'web';
SELECT * FROM orders WHERE metadata->'items' @> '[{"sku": "A1"}]';
SELECT metadata->>'coupon' AS coupon, COUNT(*) FROM orders GROUP BY 1;

-- Update JSON field
UPDATE orders SET metadata = jsonb_set(metadata, '{source}', '"mobile"') WHERE id = '...';

MySQL

Connection

mysql -h localhost -u root -p mydb
mysql -h localhost -u root -p -e "SELECT NOW();" mydb

Key Differences from PostgreSQL

-- Auto-increment (not SERIAL)
CREATE TABLE users (
    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
    email VARCHAR(255) NOT NULL UNIQUE,
    name VARCHAR(255) NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

-- JSON type (MySQL 5.7+)
CREATE TABLE orders (
    id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
    user_id BIGINT UNSIGNED NOT NULL,
    metadata JSON,
    FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
);

-- Query JSON
SELECT * FROM orders WHERE JSON_EXTRACT(metadata, '$.source') = 'web';
-- Or shorthand:
SELECT * FROM orders WHERE metadata->>'$.source' = 'web';

Query Patterns

Joins

-- Inner join (only matching rows)
SELECT u.name, o.total, o.status
FROM users u
INNER JOIN orders o ON o.user_id = u.id
WHERE o.created_at > '2026-01-01';

-- Left join (all users, even without orders)
SELECT u.name, COUNT(o.id) AS order_count, COALESCE(SUM(o.total), 0) AS total_spent
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
GROUP BY u.id, u.name;

-- Self-join (find users with same email domain)
SELECT a.name, b.name, SPLIT_PART(a.email, '@', 2) AS domain
FROM users a
JOIN users b ON SPLIT_PART(a.email, '@', 2) = SPLIT_PART(b.email, '@', 2)
WHERE a.id < b.id;

Aggregations

-- Group by with having
SELECT status, COUNT(*) AS cnt, SUM(total) AS revenue
FROM orders
GROUP BY status
HAVING COUNT(*) > 10
ORDER BY revenue DESC;

-- Running total (window function)
SELECT date, revenue,
    SUM(revenue) OVER (ORDER BY date) AS cumulative_revenue
FROM daily_sales;

-- Rank within groups
SELECT user_id, total,
    RANK() OVER (PARTITION BY user_id ORDER BY total DESC) AS rank
FROM orders;

-- Moving average (last 7 entries)
SELECT date, revenue,
    AVG(revenue) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma_7
FROM daily_sales;

Common Table Expressions (CTEs)

-- Readable multi-step queries
WITH monthly_revenue AS (
    SELECT DATE_TRUNC('month', created_at) AS month,
           SUM(total) AS revenue
    FROM orders
    WHERE status = 'paid'
    GROUP BY 1
),
growth AS (
    SELECT month, revenue,
           LAG(revenue) OVER (ORDER BY month) AS prev_revenue,
           ROUND((revenue - LAG(revenue) OVER (ORDER BY month)) /
                 NULLIF(LAG(revenue) OVER (ORDER BY month), 0) * 100, 1) AS growth_pct
    FROM monthly_revenue
)
SELECT * FROM growth ORDER BY month;

-- Recursive CTE (org chart / tree traversal)
WITH RECURSIVE org_tree AS (
    SELECT id, name, manager_id, 0 AS depth
    FROM employees
    WHERE manager_id IS NULL
    UNION ALL
    SELECT e.id, e.name, e.manager_id, t.depth + 1
    FROM employees e
    JOIN org_tree t ON e.manager_id = t.id
)
SELECT REPEAT('  ', depth) || name AS org_chart FROM org_tree ORDER BY depth, name;

Migrations

Manual Migration Script Pattern

#!/bin/bash
# migrate.sh - Run numbered SQL migration files
DB_URL="${1:?Usage: migrate.sh <db-url>}"
MIGRATIONS_DIR="./migrations"

# Create tracking table
psql "$DB_URL" -c "CREATE TABLE IF NOT EXISTS schema_migrations (
    version TEXT PRIMARY KEY,
    applied_at TIMESTAMPTZ DEFAULT NOW()
);"

# Run pending migrations in order
for file in $(ls "$MIGRATIONS_DIR"/*.sql | sort); do
    version=$(basename "$file" .sql)
    already=$(psql "$DB_URL" -tAc "SELECT 1 FROM schema_migrations WHERE version='$version';")
    if [ "$already" = "1" ]; then
        echo "SKIP: $version (already applied)"
        continue
    fi
    echo "APPLY: $version"
    psql "$DB_URL" -f "$file" && \
    psql "$DB_URL" -c "INSERT INTO schema_migrations (version) VALUES ('$version');" || {
        echo "FAILED: $version"
        exit 1
    }
done
echo "All migrations applied."

Migration File Convention

migrations/
  001_create_users.sql
  002_create_orders.sql
  003_add_users_phone.sql
  004_add_orders_metadata_index.sql

Each file:

-- 003_add_users_phone.sql
-- Up
ALTER TABLE users ADD COLUMN phone TEXT;

-- To reverse: ALTER TABLE users DROP COLUMN phone;

Query Optimization

EXPLAIN (PostgreSQL)

-- Show query plan
EXPLAIN SELECT * FROM orders WHERE user_id = '...' AND status = 'paid';

-- Show actual execution times
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT * FROM orders WHERE user_id = '...' AND status = 'paid';

What to look for:

Seq Scan on large tables → needs an index
Nested Loop with large row counts → consider Hash Join (may need more work_mem)
Rows Removed by Filter being high → index doesn't cover the filter
Actual rows far from estimated → run ANALYZE tablename; to update statistics

Index Strategy

-- Single column (most common)
CREATE INDEX idx_orders_user_id ON orders(user_id);

-- Composite (for queries filtering on both columns)
CREATE INDEX idx_orders_user_status ON orders(user_id, status);
-- Column ORDER matters: put equality filters first, range filters last

-- Covering index (includes data columns to avoid table lookup)
CREATE INDEX idx_orders_covering ON orders(user_id, status) INCLUDE (total, created_at);

-- Partial index (smaller, faster — only index what you query)
CREATE INDEX idx_orders_pending ON orders(user_id) WHERE status = 'pending';

-- Check unused indexes
SELECT schemaname, tablename, indexname, idx_scan
FROM pg_stat_user_indexes
WHERE idx_scan = 0 AND indexname NOT LIKE '%pkey%'
ORDER BY pg_relation_size(indexrelid) DESC;

SQLite EXPLAIN

EXPLAIN QUERY PLAN SELECT * FROM orders WHERE user_id = 5;
-- Look for: SCAN (bad) vs SEARCH USING INDEX (good)

Backup & Restore

PostgreSQL

# Full dump (custom format, compressed)
pg_dump -Fc -h localhost -U myuser mydb > backup.dump

# Restore
pg_restore -h localhost -U myuser -d mydb --clean --if-exists backup.dump

# SQL dump (portable, readable)
pg_dump -h localhost -U myuser mydb > backup.sql

# Dump specific tables
pg_dump -h localhost -U myuser -t users -t orders mydb > partial.sql

# Copy table to CSV
psql -c "\copy (SELECT * FROM users) TO 'users.csv' CSV HEADER"

SQLite

# Backup (just copy the file, but use .backup for consistency)
sqlite3 mydb.sqlite ".backup backup.sqlite"

# Dump to SQL
sqlite3 mydb.sqlite .dump > backup.sql

# Restore from SQL
sqlite3 newdb.sqlite < backup.sql

MySQL

# Dump
mysqldump -h localhost -u root -p mydb > backup.sql

# Restore
mysql -h localhost -u root -p mydb < backup.sql

Tips

Always use parameterized queries in application code — never concatenate user input into SQL
Use TIMESTAMPTZ (not TIMESTAMP) in PostgreSQL for timezone-aware dates
Set PRAGMA journal_mode=WAL; in SQLite for concurrent read performance
Use EXPLAIN before deploying any query that runs on large tables
PostgreSQL: \d+ tablename shows columns, indexes, and size. \di+ lists all indexes with sizes
For quick data exploration, import any CSV into SQLite: sqlite3 :memory: ".mode csv" ".import file.csv t" "SELECT ..."

SQL Toolkit

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SQL Toolkit

When to Use

SQLite (Zero Setup)

Quick Start

Schema Operations

PostgreSQL

Connection

Schema Design Patterns

JSONB Queries (PostgreSQL)

MySQL

Connection

Key Differences from PostgreSQL

Query Patterns

Joins

Aggregations

Common Table Expressions (CTEs)

Migrations

Manual Migration Script Pattern

Migration File Convention

Query Optimization

EXPLAIN (PostgreSQL)

Index Strategy

SQLite EXPLAIN

Backup & Restore

PostgreSQL

SQLite

MySQL

Tips

Quick Start

Manual Installation

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