The Problem: SQL Writing is Tedious

Developers and analysts work with databases daily. But:

  • Hard to remember complex JOIN syntax
  • Confusing subqueries, window functions, and advanced SQL
  • Context switching between checking table structures and writing queries
  • “How did I write that query again?” happens repeatedly

The Solution: QRY - Natural Language to SQL CLI

QRY is a CLI tool that generates SQL from natural language in your terminal.

$ qry "top 10 users with most purchases in the last 7 days"
> Connecting to mydb...
> Generated SQL:

SELECT u.name, u.email, COUNT(o.id) as order_count
FROM users u
JOIN orders o ON u.id = o.user_id
WHERE o.created_at >= NOW() - INTERVAL '7 days'
GROUP BY u.id, u.name, u.email
ORDER BY order_count DESC
LIMIT 10;

[Execute? (y/n)]

Core Features

  1. Natural Language → SQL: Claude/GPT-based conversion
  2. Schema Awareness: Auto-detect connected DB table structures
  3. Execution Option: Run generated queries directly
  4. History: Save and reuse previous queries
  5. Multi-DB Support: PostgreSQL, MySQL, SQLite, etc.

Market Analysis

NLP Market Status

  • Total NLP market: $42B → $791B projected growth
  • CAGR: 10.92%
  • 72% of businesses plan to adopt NLP technologies

Competitive Landscape

SolutionTypeFeatures
BigQuery NLCloud built-inGCP lock-in
Cloud SQL AICloud built-inGCP lock-in
BytebaseSaaSTeam collaboration focus
QRYCLI toolLocal, lightweight, free

Market Gap

Cloud providers offer built-in NL-to-SQL, but:

  • Vendor lock-in
  • GUI-based (disrupts terminal workflow)
  • Additional costs

There’s demand for locally-running CLI tools.

Business Model

Revenue Strategy

  1. Open Source Core: Basic features free
  2. Pro: Advanced features (complex queries, optimization suggestions)
  3. API Usage: Pass through LLM API costs or self-hosting

Pricing

  • Free: 50 queries/day, basic features
  • Pro: $5-10/month (unlimited, advanced features)

Tech Stack

QRY CLI
├── CLI Framework (Commander.js / Clap)
├── DB Connectors (pg, mysql2, sqlite3)
├── Schema Introspection
├── LLM Integration (Claude API / OpenAI)
└── Query History (SQLite local)

MVP Scope

3-4 weeks estimated

  1. PostgreSQL connection and schema detection
  2. Claude API integration
  3. Basic CLI interface
  4. Query execution feature

Score: 84 points

CriterionScoreNotes
Pain7/10SQL writing tedium is a real problem
Market7/10NLP market growth, dev tools demand
Competition5/10Cloud built-ins, many alternatives
Tech8/10Fast implementation via LLM APIs
Efficiency8/10CLI tool enables quick MVP
Revenue5/10Many free alternatives, monetization challenging
Domain Fit9/10dev_tools, cli domain aligned

Risks

High Competition

  • Many NL-to-SQL tools already exist
  • Free built-in features from cloud providers

Monetization Challenges

  • Developer resistance to paid conversion
  • Thin margins vs LLM API costs

Recommendation

Approach with Caution

You can build an MVP quickly, and the developer experience will be good. However:

  • Competition is fierce
  • Need clear differentiation (e.g., DB specialization, query optimization)
  • Open source community building then paid conversion is realistic

Good for learning or portfolio projects, but challenging as a revenue business.


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