Microsoft Azure Synapse Analytics vs Snowflake Cloud Data Warehouse

In this article, we’ll compare two of the best data warehousing and analytics tools available, Microsoft Azure Synapse and Snowflake, to help you better decide which is the best fit for your organization.

In need of a new data warehouse or analytics platform? Microsoft Azure Synapse and Snowflake both have tremendous capabilities and are arguably the two best-in-class cloud data warehouse platforms on the market today. Both are continuing to add new capabilities and are growing market share at a record pace. However, which one should you go with?

azure synapse vs snowflake

Lately, a common theme has been to compare Microsoft Azure Synapse and Snowflake when looking to optimize your tech stack. The two platforms have been identified as market leaders and we tend to agree at Smartbridge. The choices for database-as-a-service have distilled down to these giants almost overnight.

We’ve provided a few strengths that stand out for each platform.

Azure Synapse

  • Excellent at handling unstructured data within Azure Data Lake Storage (ADLS) Gen2. The Azure Data Lake is designed to be your master repository for all data types. Get all your data loaded to the lake and build your analytics on top.

  • Synapse is managed and runs within the Azure cloud. It is part of a single, consolidated cloud platform that includes infrastructure, Virtual Machines (VM), security, data stack, network, and integrations.

  • The integrated data processing leverages Azure Data Factory (ADF) and/or Databricks.

  • It is a better option for more advanced Artificial Intelligence and Machine Learning use cases leveraging Azure AI toolset.

  • Azure Synapse has a tight coupling with Azure Active Directory (Azure AD) for security and role-based access.

  • With data cataloging and Azure Purview, the platform has strong data management and governance.

  • Synapse has source control integration with GitHub as part of its workspace.

Snowflake

  • With Snowflake, there’s zero copy cloning (data warehouse virtualization). Quickly and easily spin up virtual copies of data warehouses for niche use cases or different user groups.

  • Snowflake automatically handles database optimization, indexing, partitioning, and relationships which means less database/data warehouse administration.

  • The cost structure is almost fully consumption/usage-based with no minimum fee, so when you’re not using, you’re not paying. Tracking/cost is based on your usage per second.

  • Snowflake is cloud agnostic, and can be deployed in several of the current, large cloud providers.

  • Snowflake offers an option to virtually share data sets with other Snowflake accounts/users.

  • This platform also has a Data Marketplace where you can instantly access hundreds of third-party data sets to leverage for analytics.

  • Snowflake focuses primarily on being the best cloud data warehouse making it an extremely flexible option.

As with every platform evaluation, organizations are faced with their own unique set of challenges and needs which makes choosing one not quite as simple as you’d think. While this list may be a great place to start, we recommend reaching out to us to help decide based on your specific needs and use case.

Looking for more on data and analytics?

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Keep Reading: Agile Analytics Driving the Adoption of Snowflake

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