Most companies running cloud databases are overspending — and don't have visibility into where.
The finance team sees a growing bill. The engineering team sees slow queries. Neither can answer: "Which query is driving this cost?"
FinOps tools track infrastructure costs. Database monitoring tools track query performance. Neither puts a dollar amount on an individual query. That's the gap QueryWise was built to close.
QueryWise attributes cloud database costs to individual queries, pipelines, and AI workloads across major vendors: AWS, GCP, Azure, Snowflake, Databricks, MongoDB Atlas, Redshift, Synapse, Cosmos DB, Oracle Cloud, Microsoft Fabric, and ClickHouse. One dashboard. No agents. Read-only credentials.
What you get:

Per-query cost attribution tied to actual billing data
Anti-pattern detectors across queries, pipelines, and AI workloads
AI-generated recommendations with SQL fixes and estimated savings
Pipeline/ETL cost tracking across cloud services
AI/LLM cost tracking by model and vendor
What-if scenario planning and commitment coverage dashboards
FOCUS-standard export, tag allocation, and chargeback reports

Built by InstaQuery LLC — a database performance and cloud cost consulting firm. Every detector and recommendation came from real client engagements.
Currently in design partner phase, working with teams that want clearer visibility into their cloud database spend.
🌐 querywise.io

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