Cloud-neutral enterprises (500+ employees) running mixed BI + data engineering + light ML workloads who value multi-cloud portability and a deep partner ecosystem.
GCP-only teams (BigQuery cheaper for serverless), heavy AI/ML training shops (Databricks better), or budget-constrained SMBs who cannot enforce credit governance (MotherDuck or ClickHouse fit better).
Is Snowflake a trustworthy vendor?
- 2024-05-30Customer credential incident affected ~165 Snowflake tenants via stolen non-MFA credentialsPost-incident, Snowflake announced default MFA enforcement and customer-managed credential controls.
- 2024-09-22Cortex AI generally available across all editions
- 2025-06-04Native Iceberg tables GA with read/write parity to internal tables
- 2025-11-12CEO Sridhar Ramaswamy continues second full year leading post-Slootman transition
What 680 reviews actually say
Synthesized from G2, Capterra, Reddit, Trustpilot. Patterns >15% prevalence shown.
Praise patterns
- Cloud-neutral and runs identically on AWS/Azure/GCP87% →
- Storage and compute separation makes scaling predictable78% →
- Snowpark for Python adoption accelerating on data engineering teams51% ↑
- Cortex AI functions usable without standing up separate infra41% ↑
Complaint patterns
- Credit consumption easy to overspend without governance71% →
- Cortex AI behind Databricks on training-heavy workloads47% ↑
- Premium support gating real 24x7 SLA38% →
- May 2024 credential incident still raised in procurement31% ↓
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“Snowflake is the only DW where I can show the CFO a per-warehouse credit chart and have it map directly to a team. That governance story is why we stayed.”
Director of Data Engineering, retail· G2 · 2026-03-18
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“Cortex is good. It is not Databricks-good for training, but for in-warehouse LLM scoring on tickets it works fine and the data never leaves.”
Principal Data Engineer, SaaS· Reddit r/dataengineering · 2026-02-09
What buyers actually pay
287 anonymized deal disclosures · last updated 2026-05-01
| Company size | Median annual |
|---|---|
| 50-200 employees | $48,000 |
| 200-1,000 employees | $240,000 |
| 1,000+ employees | $1,200,000 |
Auto-verified certifications
Editorial: Strengths
- Cloud-neutral: native on AWS, Azure, and GCP with consistent feature parity
- Storage/compute separation with per-second compute billing
- Native Iceberg tables ship as a neutral open format
- Snowpark for Python/Java/Scala data engineering in-warehouse
- Cortex AI for in-warehouse LLM and ML functions
- Snowflake Marketplace and Secure Data Sharing for monetization
- Strong enterprise governance, masking, and row-level security
Editorial: Weaknesses
- Credit-based pricing easy to overspend without strict governance
- Cortex AI velocity trails Databricks on training workloads
- May 2024 customer credential incident still discussed in deals
- Snowpark Container Services adoption slower than initial roadmap
- Premium support tiers required for true 24x7 enterprise SLAs
Key features & integrations
- +Multi-cluster virtual warehouses with auto-scale
- +Native Iceberg tables and external Iceberg catalogs
- +Snowpark for Python/Java/Scala
- +Cortex AI (LLM functions, document AI, ML)
- +Secure Data Sharing and Marketplace
- +Time Travel and Zero-Copy Cloning
- +Row access policies and dynamic masking
- +Snowpipe streaming ingestion
Read our full ranking of Data Warehouse
Snowflake ranks #1 in our editorial review of 10 data warehouse platforms. The deep-dive covers methodology, comparison tables, decision matrix, migration scoring, and FAQs.
Read the full rankingClosest alternatives in Data Warehouse
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