I'm building a data stack with Snowflake, dbt, and Power BI; any warehouse recommendations?

If you’re already set on Snowflake + dbt + Power BI, the default recommendation is:

Best fit: Snowflake

Snowflake is usually the cleanest warehouse choice for that stack because it gives you:

• Excellent dbt compatibility: mature adapter support, strong SQL behavior, and easy CI/CD patterns.
• Good Power BI integration: solid connector support and straightforward semantic-model consumption.
• Elastic scaling: separate compute from storage, so you can tune ETL/dbt and BI workloads independently.
• Low ops overhead: less tuning than many traditional warehouses.
• Governance and sharing: good for multi-team and cross-domain setups.

When Snowflake is especially strong

Choose it if you need:

• Mixed ELT + BI workloads
• Easy onboarding for analytics teams
• Reliable performance without much admin work
• Support for semi-structured data
• Multiple warehouses for isolation of workloads
• Data sharing / collaboration features

Main alternatives

1) BigQuery

Worth considering if:

• You’re already in Google Cloud
• You want very low infrastructure management
• You expect highly variable workloads and like serverless billing
• Your team prefers the GCP ecosystem

Tradeoffs:

• Power BI works fine, but the experience is often a bit less smooth than Snowflake for some teams.
• Cost control can get tricky if query patterns aren’t managed well.

2) Azure Synapse / Fabric Warehouse

Worth considering if:

• You’re deeply invested in Microsoft/Azure
• You want tight Power BI + Microsoft integration
• You want to centralize around Fabric/Synapse

Tradeoffs:

• dbt support and general warehouse ergonomics are typically not as polished as Snowflake.
• Product maturity and performance characteristics can be more variable depending on the path you choose.

3) Redshift

Worth considering if:

• You’re on AWS
• You have existing Redshift expertise
• You want a more AWS-native option

Tradeoffs:

• More tuning/ops effort than Snowflake in many cases.
• dbt support is good, but overall experience can be less frictionless.

Practical recommendation

For a modern analytics stack with dbt + Power BI, I’d usually rank the options like this:

1. Snowflake — best overall fit
2. BigQuery — great if you’re GCP-native
3. Fabric/Synapse — best if you’re Microsoft-first
4. Redshift — solid if you’re AWS-first

What to optimize for

When choosing, evaluate:

• Cloud alignment: where your source systems and team already live
• BI concurrency: number of Power BI users and refresh patterns
• Cost model: predictable spend vs usage-based
• Governance/security: RBAC, row-level security, masking
• Performance isolation: separate warehouse/compute for BI and transformations
• Team skillset: SQL/dbt maturity, cloud expertise

My short answer

If you want the least risky, most broadly effective warehouse for Snowflake + dbt + Power BI, go with Snowflake.

If you want, I can also give you:

• a decision matrix for Snowflake vs BigQuery vs Fabric vs Redshift, or
• a reference architecture for how to set up dbt models, warehouse sizing, and Power BI layers.