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🌎 DataBot — Optimizing Databases for a Greener World

💭 Inspiration

Convenience and consumerism — two forces that now drive our world — have caused us to ignore the massive footprint we leave behind with every digital action.

We treat "the cloud" like some magical place where everything (photos, videos, data of all sorts) exists, without thinking about the energy it takes to operate it all.
In reality, massive data centers run 24/7, burning through staggering amounts of electricity and resources.

Out of sight, out of mind... right?
That mindset is dangerous.

While we often blame transportation and agriculture for climate problems, the digital world is becoming a growing, silent contributor — and nobody talks about it.

⚡ Poorly optimized databases → More CPU cycles → More RAM usage → More disk I/O → More server load → Higher carbon footprint.

Sustainability needs to become a normal part of infrastructure development, not just an afterthought.

🤔 What it Does

DataBot is a powerful app that reveals slow queries, storage bloat, unused data, and an overall green score (representing how energy-optimized your database is) — all in one place.
It doesn't just show problems — it actively optimizes your databases to be faster and more environmentally responsible.

🌟 Features

📈 Optimization

Slow Query Detection
- Find and flag slow queries.
- Suggest faster alternatives (e.g., missing indexes, bad joins, unnecessary subqueries).
AI-Powered Query Rewrite Suggestions
- Google Gemini suggests faster, cleaner, greener SQL query versions.
Caching Recommendations
- Recommend using cache layers (Redis, Memcached) to reduce direct database load.

💾 Database Storage Optimization

Index Optimization
- Find missing indexes.
- Remove unnecessary indexes that slow down write operations.
Duplicate Data Detection
- Identify identical or highly redundant data entries.
Unused Table/Column Detection
- Highlight dead weight: tables or columns not accessed in a long time.

🔄 Data Lifecycle Management

Data Compression Recommendations
- Suggest compressed formats for large blob/text fields to save storage and energy.
Auto-Partitioning
- Propose or auto-generate SQL for partitioning large tables to speed up queries.

🌍 Environmental Impact Metrics

CO2 Savings Calculator
- Estimate how much carbon emissions (g/month) are saved after optimization.
Energy Usage Estimation
- Show users estimated kWh saved based on optimizations.
Green Score for Databases
- Assign an intuitive "green report card" to databases based on optimization levels.

✨ Users can also chat directly with an AI database assistant to ask questions like:

"Analyze my database and tell me where I'm wasting the most energy."

📚 Currently Supported Databases:
MongoDB • PostgreSQL • MySQL

🔨 How We Built It

Backend: Go • Google Gemini API
Frontend: Next.js • React • TailwindCSS • TypeScript
Database: Modular architecture to support multiple engines

The AI agent (powered by Gemini) connects directly to your database, automatically detecting inefficiencies and suggesting optimizations in real time.

💪 Challenges We Ran Into

Query Parsing Complexity: Nested subqueries, CTEs, and advanced SQL features made parsing and improving queries tricky.
Measuring CO2 Impact: Different data centers have different efficiencies. We approximated using best practices, but precision remains a challenge.
Supporting Multiple Database Engines: PostgreSQL, MySQL, and MongoDB each have unique quirks, requiring us to make modular, flexible codebases.

🏆 Accomplishments We're Proud Of

Making Sustainability Easy: We brought attention (and a solution) to an often-ignored part of digital sustainability.
Raising Awareness: Every developer who sees this project leaves a little more conscious about the environmental impact of infrastructure inefficiencies.

🎓 What We Learned

Optimization Isn't Just About Speed: True optimization considers both performance, cost, and environmental impact.
Metrics Matter: People need to see tangible results (CO2 savings, kWh savings) to stay motivated to optimize.
Sustainability Should Be Built In: Green engineering needs to become a core pillar of software and infrastructure design.

🔜 What's Next for DataBot

➡️ Support for More Databases:
(Redis, Neo4j, DynamoDB, etc.)
➡️ Database Fitness Tracker:
(Green Score, query speeds, storage use visualized over time with graphs and dashboards)
➡️ Real-time Smart Alerts:
(Automatic alerts if a query or storage usage spikes)
➡️ Cold Storage Automation:
(Move unused data into nearline/cold storage like Google Nearline or Amazon Glacier)