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:
- Initial query → Runs on your data warehouse to fetch data
- Further queries (100MB-32GB) → Run on Count's servers using DuckDB
- 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
- Query execution model - How Count runs queries
- DuckDB in Count - Local compute engine
- Performance optimization - Writing efficient queries
Using the Compute layer with Count Metrics
- Count Metrics overview - Governed data models
- Query performance & optimisations - When data is cached vs. live