Supercharge your data team

Automated infrastructure management is here

InQuery uses AI to tune your Trino or Spark cluster performance while reducing lakehouse cloud costs.

Optimizing your data platform is hard

Enterprise lakehouse deployments suffer from...

High

Server costs

Query latency

Management overhead

Low

Resource utilization

System visibility

InQuery saves you time and money with easy-to-use lakehouse optimizations

Effortless lakehouse monitoring and observability

InQuery monitors query traffic from source to target, giving you detailed visibility into your cluster’s health and performance.

Automated query-level optimizations

InQuery identifies SQL anti-patterns and intelligently routes queries at runtime to ensure fast and efficient execution.

Powerful system reports

InQuery analyzes your query traffic and surfaces opportunities to tune query engine and storage knobs.

How It Works

InQuery simplifies data lakehouse maintenance, saving your data team time and money.

Today, InQuery focuses on helping you manage and optimize your Trino deployment to achieve better performance and cost efficiency at scale.

InQuery provides online and offline system analysis to help you monitor, debug, tune, and optimize your system to ensure that your infrastructure resources are used efficiently, helping you cut costs and ensure a snappy experience for your users.

Our Team

Meet Our Founders

We’re a deeply technical team that loves to build delightful software experiences for our customers.

Erick Enriquez

Cofounder @ InQuery

Software Engineer on DoorDash's Data Platform
Founding Software Engineer at Hearth
B.S. Mathematical and Computational Sciences at Stanford
Khalil Miri

Cofounder @ InQuery

Quantitative Trader at DRW
B.S. Computer Science at Stanford