Count's compute layer

Count's compute layer intelligently routes queries between your data warehouse, Count's servers, and users' local machines—reducing warehouse costs while enabling faster, more exploratory analytics.

#Why the compute layer matters

The problem: Every query to your data warehouse costs money and takes time. BI tools can consume 30-80% of warehouse costs. When AI agents get involved (running 15+ queries per question), costs can explode.

The solution: Run queries where it makes most sense. Small and medium queries run locally or on Count's servers. Only large initial queries hit your warehouse. Result: 60%+ of queries never touch your warehouse.

#How it works

Query routing:

  1. Initial query → Runs on your data warehouse to fetch data
  2. Further queries (100MB-32GB) → Run on Count's servers using DuckDB
  3. Small queries → Run directly on user's laptop using DuckDB

What this means:

  • Once data is pulled from your warehouse, you can iterate, filter, aggregate, and analyze without additional warehouse queries
  • AI agents can run unlimited queries for thorough analysis without cost concerns
  • Everyone can explore data freely without worrying about warehouse bills

Benefits:

  • Up to 80% reduction in BI tool warehouse costs
  • Faster query performance (local compute is faster than warehouse round-trips)
  • Enables exploratory, iterative analysis without throttling
  • Still leverage warehouse for large queries when needed

#Who benefits

Data teams:

  • Iterate freely on analyses without cost concerns
  • Work with AI agents that can dig deep without limitations
  • Faster performance for exploration and refinement

Business users:

  • Explore data without needing to understand warehouse costs
  • Use self-service analytics safely and affordably

Finance/platform teams:

  • Reduce data warehouse spend
  • Enable broader data access without cost explosion
  • Predictable costs even with increased usage

#Learn more

#Understanding the compute layer

#Using the Compute layer with Count Metrics

Last updated: 05/08/26