Compare
AWS Clean Rooms vs Snowflake Data Clean Rooms
Both keep each party's raw data on its own cloud platform; AWS publishes an itemized rate card and differential privacy, Snowflake bills via compute credits.
Side by side
| AWS Clean Rooms | Snowflake Data Clean Rooms | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Vendor | Amazon Web Services | Snowflake Inc. | ||||||||
| Pricing model | Usage-based | Usage-based | ||||||||
| Free tier | No | No | ||||||||
| Deployment | Cloud | Cloud | ||||||||
| Open source | No | No | ||||||||
| Best for | AWS-centric organizations running two-party or multi-party analysis without moving data off AWS. | Two Snowflake customers who want to collaborate without adopting a separate third-party clean room product. | ||||||||
| Pricing | Billed per Clean Rooms Processing Unit (CRPU) hour for SQL/Spark, with add-on rates for differential privacy, ML and entity resolution.
Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget. | No separate clean-room price list; billed through standard Snowflake compute credits based on warehouse usage. Pricing has not been verified yet — see the vendor's site. | ||||||||
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Verdict
AWS Clean Rooms and Snowflake Data Clean Rooms solve the same problem the same way: each collaborator's raw data stays inside its own account on that platform, and governed, templated queries run across both accounts to return only approved results. Neither requires either party to copy data onto a third-party service. The real choice, in most cases, is already made by which platform both organizations use — this is a same-cloud decision more than a feature decision.
Where they differ is depth of published detail and add-on options. AWS Clean Rooms has an itemized, public rate card down to the compute-unit-hour, plus an explicit differential privacy option that adds quantified statistical noise to outputs. Snowflake's clean room capability is a feature built on existing Secure Data Sharing infrastructure, billed through ordinary Snowflake compute credits with no separate clean-room line item.
Choose AWS Clean Rooms if
- Both collaborators already run on AWS, and you want a documented, itemized cost structure before committing.
- The use case needs a formal, quantified privacy guarantee — the differential-privacy add-on is a specific, named feature here.
- You also want AWS Clean Rooms ML (lookalike modeling) or AWS Entity Resolution for identity matching in the same workflow.
Choose Snowflake Data Clean Rooms if
- Both collaborators already store their data in Snowflake, and you'd rather avoid standing up a separate clean-room product.
- Your organization is comfortable with cost scaling through standard Snowflake compute credits rather than a dedicated rate card.
- You want to reuse Snowflake's existing row- and column-level security policies and RBAC rather than learning a new access model.
The honest caveat
Neither of these is a good fit if your counterparty is on the other cloud — a Snowflake shop collaborating with an AWS-native partner that isn't also in Snowflake will find Snowflake's clean room inapplicable, and vice versa for AWS. For genuinely cross-platform collaboration, a purpose-built multi-cloud clean room such as LiveRamp Clean Room or Decentriq is the more honest comparison, not this pair.
Last reviewed September 22, 2026