Alder uses LLM-powered Agents to automatically optimize complex data warehouse queries. It builds a virtual runtime, finds bottlenecks, rewrites queries, evaluates improvements, and delivers the best plan—cutting manual tuning costs to zero.
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⋆✦* We’re live! Autonomous query performance optimization — powered by AI Agents.
👋 Hey Product Hunt! We’re the team behind Alder, and we’re thrilled to launch a new kind of performance tuning platform — one built specifically for complex data warehouse workloads, and powered entirely by LLM Agents.
⋆✦* With Alder, you get:
✅ Fully autonomous query optimization—no manual tuning required
✅ AI Agent–built runtime simulates real query execution
✅ Bottleneck detection and root cause analysis
✅ Smart query rewrites, execution plan tuning, and DDL suggestions
✅ All optimization strategies are evaluated in simulation, ensuring semantic correctness and performance gains
✅ Secure and privacy-preserving—no need to access your data
✅ Available as a SaaS or private deployment
⋆✦* Why we built Alder:
Tuning data warehouse queries is high-stakes, high-cost, and often left to a few experts. In large-scale warehouses like Snowflake, PostgreSQL, or Greenplum, even small inefficiencies can lead to massive costs. Yet, the tuning process remains manual, slow, and brittle.
We built Alder to fully automate this process using multi-agent systems and LLMs — combining expert-level decision-making with scalable automation. Our goal: cut query tuning cost to near-zero, and make performance engineering accessible to every team.
🎉 This is our early preview release, and your feedback means everything to us!
We’re actively refining Alder and would love to hear your thoughts, ideas, and suggestions. Try it out at http://www.alderintelligence.com/, and let us know what features, improvements, or crazy ideas you’d like to see next!
We’ll be hanging out here all day—ask us anything about AI, databases, and performance tuning!
Cheers from the Alder team! 🙌
@alder_intelligence I'm very happy to see a product like Alder that applies AI to the database optimization field, solving a major challenge in our daily work.
@alder_intelligence What databases do we support? Do you have plans to support Snowflake in the future?
Currently we support PostgreSQL and Greenplum which is a MPP data warehouse based on PostgreSQL, will support Cloud Data warehouse like Snowflake, Redshift soon.
It's easy to use, upload the minirepo and wait one minute. Then the query is optimized!
Here is what I got:
Optimization Summary: The query was optimized by applying a Common Table Expression (CTE) to calculate the average quantity only once, instead of executing a subquery multiple times. This change significantly reduced the execution cost and improved performance.
Expected Performance Improved Ratio: 1543.99X
Original Plan: The original query plan involved a Hash Join with a subquery that was executed for each row, leading to high costs. The optimized plan uses a Parallel Hash Join and aggregates the average quantity beforehand, resulting in a more efficient execution.
It's Great!
Just spent the hours testing Alder and I'm genuinely impressed. As someone who regularly battles with slow data warehouse queries, this is a game-changer. The AI agent caught optimization opportunities I completely missed and rewrote my most problematic query, cutting execution time nearly in half!
What I appreciate most is that it doesn't just hand you optimized code - it walks you through the reasoning behind each change, which has actually improved my SQL skills. The setup was surprisingly painless with our existing environment.
Really cool to see how they've leveraged the MetaGPT framework to create specialized agents for database optimization. For teams dealing with complex queries and large datasets, this is definitely worth adding to your toolkit. Solid work, team!
Super impressive — love how you're using AI agents to tackle query optimization 🔍
Here to support your launch today!
The optimized query shows a high improvement ratio while ensuring correctness and equivalence. The analysis and visualization features are also great - the overall experience is excellent, and I'll definitely use it more often.
I really like the style of this UI, especially the way it displays the query plans before and after optimization. However, what interests me the most is the automated agent, and I'm looking forward to it being available for direct use on the website.
Great product, it's very helpful and easy to use for query optimization.