Chen Cuello
JUL 29, 2023
5 min read
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All businesses dealing with large data influxes need high-end data storage or a warehouse that prepares them for further analytics. The market is flooded with cloud-data warehousing platforms, but the most opted and trusted ones are Snowflake and Amazon Redshift.

These two warehousing platforms offer more or less the same features, including security, scalability, relational management, and cost efficiency, that allow businesses to scale and offer outstanding performance. However, the main differences between these two are the deployment options, pricing models, and overall user experience.

In this article, we will compare Redshift vs. Snowflake performance, features, use cases, analytics, and much more to see which one is the better option and how it applies to businesses. 

Overview of Redshift and Snowflake

Snowflake is among the first warehousing platforms that could offer almost unlimited analytical scale, workload isolation, and horizontal use scalability. It’s multi-tenant through the shared resources in nature and requires the use to relocate the data from a personal VPC into the Snowflake cloud. Otherwise, Snowflake operates on AWS, Axure, and GCP.

Unlike Snowflake, Redshift operates on older architecture that cannot separate the data and compute or analyze it. Nowadays, it has RA3 nodes that allow users to scale and compute but cache only local data.

Note that separating and isolating different workloads of the same data is impossible on Redshift. However, users have a serverless option with Redshift based on a unit called Redshift Processing Unit that ranges from 8–512 in increments of 8.

To better compare the Redshift vs. Snowflake warehousing platforms, we need to explore the performances, features, and costs. 

Redshift vs. Snowflake Performance

To get a comprehensive Redshift vs. Snowflake comparison, we must first focus on their performance and elaborate more on it in terms of speed, reliability, and scalability. 

Redshift offers amazing performance because of the internal networking components. It uses a high-bandwidth connection, custom communication protocols, and proximity. Consequently, the system reaches high-speed communication between the nodes. 

Nodes are integral parts of a cluster that a cloud data warehouse cannot operate without. These are divided into slices, and in every slice, a portion of the node’s memory and disk space is allocated. Thanks to these nodes, Redshift can neutralize the workload of a node and offer you an optimized query performance. As you provision a cluster, you can upload data sets and start with data analysis queries.

Similarly, Snowflake is composed of database storage (including managing information in terms of data size, metadata, and structure) and query processing through virtual warehouses. These so-called virtual warehouses are basically cluster nodes and cloud services. The cloud services link the infrastructure management, query parsing, authentication, and access control.

Snowflake is also a super fast and more flexible data warehouse because it divides its computing and storage functions in the pricing plan.

Snowflake vs. Redshift Cost

When it comes to Snowflake vs. Redshift Cost, both platforms offer different pricing plans, but we can denote that Redshift is less expensive. 

Redshift doesn’t have a fixed pricing system, but it calculates the total cost based on the node used per hour. You can calculate your monthly costs by multiplying the price per hour, cluster, and monthly hours.

Similarly, Snowflake doesn’t offer a fixed pricing system, and it charges depending on the hour spent for each virtual data warehouse. However, you should know that the data storage costs are divided by the initial costs. 

Luckily, both Redshift and Snowflake offer discounts from 30% to 70%.

Snowflake vs. Redshift Features

Communication with clients through Snowflake is automatic, and you don’t need to copy any data and then share it with different accounts. This may be one of the main advantages when it comes to the features comparison of Amazon Redshift vs. Snowflake

Although there are some data exchange services, Redshift doesn’t support semi-structured data types without extensions.

As for the strings, Redshift caps data types to 65535 characters, whereas Snowflake limits the strings to 16 MB. 

Speaking of security, both Snowflake and Redshift offer robust security systems. You can find extra features and tools with Redshift, such as cluster encryption, cluster security case, data in transit, load data encryption, etc. Plus, you can limit the access in Redshift and control data usage.

Snowflake, on the other hand, offers similar security options, but they are not available across all versions. You have to choose the version that has it all to have total control over the platform.

Snowflake vs. Redshift Use Cases

Snowflake is the platform with more support for JSON-based functions compared to Reshift. In this part of our Snowflake vs. Redshift review, we can denote that Snowflake is the leader. It’s more automated in maintenance compared to Redshift. However, Reshift fits better with Amazon’s cloud of services.

We have to mention that Redshift is an excellent option when it comes to real-time analytics that can stream through different sources. Many businesses use Redshift during important decision-making processes because it allows them to process the data and adapt to the new changes in the market.

Snowflake vs. Redshift Gartner

According to Gartner, the Snowflake vs. AWS Redshift is almost a tie, with a small lead from Snowflake. Out of 1171 real user testimonials, Redshift receives a high ranking of 4.4, whereas Snowflake has 4.6. 

Regarding the main features and performances, here are the following findings according to the ratings:

  • Scalability: Snowflake leads on the scalability services with a rating of 4.7.
  • Integration: During integration, Redshift leads with 4.5, which is surprising because the integration features are top-notch.
  • Customization: Since both platforms are highly customizable, they receive an equal mark of 4.2.
  • Ease of deployment, administration, and customization: Both platforms are user-friendly, and almost everything is below their fingertips, but Snowflake leads with 4.6 over 4.5.

Snowflake vs. Redshift Cost Comparison

We already detailed the differences and similarities between these two tools when it comes to their costs. However, seeing that the price is always the first thing customers check, we decided to give a completely transparent look at the costs. 

Since both platforms don’t have a fixed plan but go on a “you pay for what you use” basis, we used their generators to come up with a plan for both options. For that purpose, we chose the US (East Ohio) as a region and AWS as a platform. Here are the results:

Standard Plan$2 per creditDense Compute DC2: 
Enterprise$3 per creditdc2.large (2 vCPU, 15GiB, 0.60 GB/s)

dc2.8xlarge (32 vCPU, 244 GiB, 7.50 GB/s)

$0.25 per hour

$4.80 per hour

Business Critical$4 per creditRA3 with Redshift Managed Storage:
Virtual Private SnowflakeUpon arrangementra3.xlplus (4 vCPU, 32 GiB, 0.65 GB/s)

ra3.4xlarge (12 vCPU, 96 GiB, 2 GB/s)

ra3.16xlarge (48 vCPU, 384 GiB, 8 GB/s)

$1.086 per hour

$3.26 per hour

$13.04 per hour


  • On-demand storage: $40 per TB/per month
  • Capacity storage: $23 per TB/per month

  • From $0.29 to $0.44, depending on the add-on.

Both options have trial periods. Snowflake offers 30 days, whereas Redshift has 750 hours.

Redshift Aqua vs. Snowflake

When comparing Redshift Aqua vs. Snowflake, Snowflake offers immediate scaling, while users of Redshift take a few minutes to add more nodes. Additionally, Snowflake operates with more automated maintenance than Redshift. 

There is less need for manual maintenance in Snowflake than in Redshift, but Redshift integrates with Amazon cloud services. Plus, built-in security is better than Snowflake. However, the updated version of Snowflake SQL has an updated autocomplete feature.

Redshift Spectrum vs. Snowflake

As mentioned above, Snowflake divides the compute usage from storage, while Redshift joins it. Furthermore, Snowflake allows users daily amount or charging by the second once a usage exceeds it. It offers instant scaling, whereas Redshift takes minutes. 

However, this is sped up by Redshift’s Spectrum feature. It allows the data warehouse to conduct fast analysis of complex data stored in the cloud. This means you can use the nodes in every cluster or get the quantity of the bytes scanned. 


We have mentioned that both warehousing platforms offer similar features and services, but they still differ in some points. For starters, the pricing plans of both platforms are super flexible. Redshift charges are per hour, whereas Snowflake charges per credit, so if your company is still developing, Snowflake may be a better option.

However, when it comes to the final say, it all depends on the organization’s needs. For example, Redshift is perfect for all companies looking for a more traditional warehousing approach, whereas Snowflake is suited and organized as a cloud-native solution.

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