Prompt
What warehouse should I use for Salesforce, Stripe, and product events?
Latest observation
A good default choice is BigQuery if you’re on Google Cloud, or Snowflake if you want the most common cross-cloud enterprise option. For Salesforce, Stripe, and product events, I’d usually recommend:
Best overall fit: Snowflake
Why:
- Handles SaaS + event data well
- Easy to combine CRM data (Salesforce), billing data (Stripe), and product analytics/events
- Strong ecosystem of ELT tools like Fivetran, Airbyte, dbt
- Good for analytics, modeling, and sharing data across teams
If you’re already in Google Cloud: BigQuery
Why:
- Very good for high-volume product event data
- Low ops overhead, easy to scale
- Excellent if you use GCP-native tools
- Often cheaper/easier for heavy query workloads on event data
If you want the simplest “modern stack” pattern
A common setup is:
- Salesforce + Stripe → ingest with Fivetran or Airbyte
- Product events → send through Segment, RudderStack, or direct ETL into the warehouse
- Warehouse → Snowflake or BigQuery
- Transformations → dbt
Quick recommendation by company type
- Startup / GCP-heavy → BigQuery
- Mid-market / multi-tool / future-proof → Snowflake
- Already on AWS and want analytics lakehouse-style setup → consider Redshift or Databricks, but these are less universally convenient for this use case
My practical recommendation
If you want one answer: Snowflake is usually the safest choice for Salesforce + Stripe + product events.
If you want, I can also recommend:
- the best warehouse based on your cloud provider,
- the cheapest option, or
- a full reference architecture for ingesting Salesforce, Stripe, and product events.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
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OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
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