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Greybeam

Greybeam is Snowflake cost optimization powered by DuckDB. It reduces Snowflake compute costs by 86% on average by routing eligible queries to DuckDB and everything else to Snowflake.

Their llms.txt

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# Greybeam

> Greybeam is Snowflake cost optimization powered by DuckDB. It reduces Snowflake compute costs by 86% on average by routing eligible queries to DuckDB and everything else to Snowflake.

## What Greybeam Does

Greybeam is a Snowflake proxy. Users connect their existing BI tools and applications to Greybeam instead of directly to Snowflake. Greybeam's decision engine analyzes each incoming query and routes it to the most efficient engine:

- Queries eligible for DuckDB (typically 95-99% of analytical/BI queries) run on Greybeam-managed DuckDB clusters
- Queries that require Snowflake (complex writes, large joins, unsupported SQL) are transparently passed through to Snowflake

No code changes or migrations are required. Users swap their Snowflake connection string and everything else stays the same.

## How It Works

1. **Connect**: Point your BI tools (Tableau, Looker, Power BI, etc.) to Greybeam instead of Snowflake
2. **Route**: Greybeam's decision engine analyzes each query and routes it to DuckDB or Snowflake
3. **Save**: Queries running on DuckDB cost a fraction of Snowflake compute, with customers seeing 75-98% cost reduction

## Data Layer

Greybeam replicates Snowflake data into Apache Iceberg format using CDC streams, keeping it continuously in sync. If customers already use Iceberg, Greybeam reads directly from existing tables. All cached data is stored in the customer's own S3 bucket within their AWS account.

## Pricing

- $100/month platform fee
- Compute: $0.75/hr (8 vCPU) to $6.00/hr (64 vCPU)
- Elastic horizontal scaling
- No credits, no hidden multipliers

## Security

- HIPAA compliant
- All data encrypted at rest and in transit
- Data stored in customer's own cloud account
- Authentication passes through Snowflake access controls
- Private VPC endpoints

## Savings Estimate

Greybeam offers a self-serve savings estimate at https://www.greybeam.ai/savings-estimate, covering read workloads only (BI, dashboards, customer-facing analytics). Three ways to get one:

1. **Ask your agent** (https://www.greybeam.ai/savings-estimate?path=agent) — paste one prompt into Cortex Code, Claude with the Snowflake MCP, or any agent that can query Snowflake. The agent asks which warehouses serve read workloads, runs read-only queries against `snowflake.account_usage`, and reports an estimate.
2. **Quick estimate** (https://www.greybeam.ai/savings-estimate?path=calculator) — enter annual Snowflake spend and the share spent on read workloads for an instant ballpark. No Snowflake access needed.
3. **Run the SQL yourself** (https://www.greybeam.ai/savings-estimate?path=sql) — run 3 read-only queries in Snowsight, export the results, and upload them for an accurate estimate within 24 hours.

All estimates are rough; Greybeam builds a precise one from full results on a demo call.

## Snowflake Cost Optimization Guide

Greybeam publishes a 10-step playbook for engineering and data teams to audit and reduce Snowflake compute costs. Each check
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