Enterprises are using leading cloud providers including GCP, Microsoft Azure and AWS, with Snowflake integration, to build modern data warehouse solutions in the cloud.

All offer highly scalable and reliable data warehouse solutions but some differences in technical details and price models are listed in the table below.

	Snowflake	Amazon RedShift	Google BigQuery	AzureSynapse
Architecture	Hybrid (Shared Disk & Shared Nothing Architecture)	Shared-nothing MPP	MPP	MPP
Database Model	Relational	Relational	Hybrid (Store Data in Columns, Support NoSQL as well)	Relational
Data Types	Structured andSemi-Structured	Structured andSemi-Structured	Structured andSemi-Structured	Structured andSemi-Structured
In-memory Capability	No	Yes	Yes	Yes
Maintenance	Fully-Managed	Fully-Managed	Fully-Managed	Required somemanual maintenance
Deployment	Cloud based	Cloud based	Cloud based	Cloud-based
Scalability	Users can scalestorage andcomputeindependently,It automaticallyadds/removesnodes.	Decoupled storage and compute withRA3 nodes.	Storage and compute scale independently. Scaling is handled automatically by BigQuery.	Serverless optionscales automatically. For the dedicatedoption, additionalstorage must beadded manually.
Analytics Ecosystem	Support major Bland Data AnalyticTools	Business Intelligence with AWSQuicksight and Integration with other Bl tools	Google Workplace,Business intelligence  with Locker	Azure ecosystems for analytics and PowerBI for business
Data Backup andRecovery	Yes	Tes	Yes	Yes
Cost	Pay for Storage and Compute Time	On-demand or Reserved Instances	On-demand andFlat-rate	Pay for Storage andCompute