Successful businesses depend on sound intelligence, and as their decisions become more data-driven than ever, it's critical that all the data they gather reaches its optimal destination for analytics: a high-performing data warehouse in the cloud.

When it comes to best-in-class data warehouse cloud solutions that run on the AWS platform, Snowflake and Amazon Redshift are top performers that have revolutionized the volume, speed, and quality of business intelligence insights. Opting for one over the other isn't so much about determining which product is superior, but identifying which solution makes the most sense for your data strategy.

Redshift vs. Snowflake - how to choose between these two leading cloud data warehouse providers?

Snowflake vs. Redshift: The details make all the difference

Key points of distinction in pricing, security, and performance inform whether Snowflake or Redshift is a better data warehouse for your business. We've discussed some of Redshift's key features before; now we'll compare it with Snowflake, and see how these two cloud data destinations differ.

Snowflake vs. Redshift

How do these two cloud data warehouse solutions compare? Here's a quick guide:


  • Pay separately for compute and storage
  • More robust support for JSON-based functions
  • Tier-based packages
  • Security and compliance options vary by tier
  • Unique architecture designed to scale on the web
  • More automated database maintenance features


  • Deep discounts on long-term commitments
  • More unified offer package
  • Security and compliance enforced in a comprehensive fashion for all users
  • Machine learning engine
  • More hands-on maintenance

Bottom line: Snowflake is a better platform to start and grow with. Redshift is a solid cost-efficient solution for enterprise-level implementations. This said — do your homework!

Pricing: Don't stop at the sticker price; consider long-term benefits

Both Snowflake and Redshift offer on-demand pricing, but package associated features differently. Snowflake separates compute usage from storage in their pricing structure, while Redshift bundles the two together. Redshift offers users a dedicated daily amount of concurrency scaling, charging by the second once usage exceeds it; concurrency scaling is automatically included with all editions of Snowflake.

Redshift boasts the potential for deep discounts over the long term if you commit to a one- or three-year contract, and offers the option to pay an hourly rate (by type and nodes in each cluster) or by the quantity of bytes scanned (a feature called Spectrum). Snowflake offers five editions with additional features tied to each ascending level of price, so you can opt out of the features that aren't a good fit for your business. Editions are determined by volume and types of data, geographical regions, and AWS or Azure platform.

When comparing the two platforms, consider what resources you need to support your business' specific data volume, processing, and analysis requirements. The right warehouse will deliver a better long-term ROI by consistently improving the speed, efficiency, and accuracy of data-driven action.

Security: Choose your warehouse wisely

While Redshift addresses security and compliance in a comprehensive fashion, Snowflake takes a nuanced approach.

Redshift's end-to-end encryption can be tailored to fit your security requirements. Additionally, you can isolate your network within a virtual private cloud (VPC) and link it to your existing IT infrastructure via VPN. Integration with AWS CloudTrail provides auditing to help you meet compliance requirements.

Snowflake boasts always-on encryption, along with VPC/VPN network isolating options, but a key differentiation from Redshift is that Snowflake's scope of security and compliance options grows more robust depending on which edition of the product you opt for — so carefully vet the edition you're considering to make sure it includes all the provisions you'll need.

Performance: New Redshift features compete with Snowflake

Both Redshift and Snowflake leverage columnar storage and massively parallel processing (MPP) for simultaneous computation, enabling advanced analytics and saving significant time on sizable jobs.

Snowflake attributes its performance to a unique architecture that supports structured and semistructured data. It keeps compute, storage, and cloud services separate to optimize their independent performance. Concurrency scaling has always been a feature of Snowflake's platform, but Redshift has recently introduced their own concurrency scaling feature, along with machine learning, to compete with Snowflake's throughput capabilities.

Each platform offers free trials and proof-of-concept support to help businesses get firsthand experience with the ways their solutions deliver value.

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Redshift vs. Snowflake: Which warehouse makes sense for you?

Further comparison between these two data warehouse solutions illustrates how they're suited for different needs:

  • Features: bundled or not? Redshift bundles compute and storage to provide the immediate potential to scale to an enterprise-level data warehouse. But by splitting computation and storage and offering tiered editions, Snowflake provides businesses the flexibility to purchase only the features they need while preserving the potential to scale.
  • JSON: dealbreaker or no big deal? When it comes to JSON storage, Snowflake's support is decidedly more robust than Redshift. This means that with Snowflake you can store and query JSON with native, built-in functions. When JSON is loaded into Redshift, it's split into strings, which makes it harder to work with and query.
  • Security: everything you could ever need, or only what your business needs? Redshift includes a deep bench of customizable encryption solutions, but Snowflake provides security and compliance features oriented to its specific editions so that you have the level of protection most relevant to your data strategy.
  • Data duties: automated or hands-on? Redshift requires more hands-on maintenance for a greater range of tasks that can't be automated, such as data vacuuming and compression. Snowflake has the advantage in this regard: it automates more of these issues, saving significant time in diagnosing and resolving issues.

Consider how optimized you'd like your data warehouse to be. Gauging these features against your data strategy will clarify whether they're pros or cons.

Whichever warehouse you choose, Stitch gets your data there fastest

Snowflake or Redshift — on the road to better business intelligence, they're both prime destinations. And no matter which one you select as your data warehouse, getting all of your data there quickly is critical to providing the background you need for better business intelligence.

Stitch is already in the express lane with an innovative, lightning-quick approach to ETL that pulls your data from more than 90 different sources to key data destinations like Snowflake and Redshift. Set up a free trial now and deliver insights to your team faster than ever before.

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