AWS vs Snowflake: Which one is best in 2024

AWS vs Snowflake Are you also finding the answer about AWS vs Snowflake: which one is best? Then worry no more. This guide is here for you! In today’s rapidly evolving world, the rise of big data has been met with a commiserate increase in computing technologies and data storage that scale effectively without costing businesses high amount. The decision to build which cloud data warehouse between AWS vs. Snowflake can be a difficult choice and involves various factors that one should considered. Cloud data warehouses are undoubtedly the best solution to cater to the scale up in overall data volume as they ensble organization to run complex queries and create a unified view and on large data sets.

If you are in the process of choosing which one of the cloud data warehouse service, we have compared AWS and Snowflake. Let’s dig into the article to discover the benefits of both data warehouses and which suits your business best.

Understanding AWS Redshift

Amazon Web Services (AWS) is the first ever public cloud provider to provide a cloud-based, data-warehousing, and petabyte-scale services. This service is called Amazon Redshift and is the one of the most famous cloud data warehouse. Amazon Redshift has been founded in 2013

Understanding Snowflake

Snowflake is founded in 2012 in San Mateo, California. It offers a cloud-based data warehouse solution for analytics and data storage, utilizing a centralized repository for data insights. The platform supports the ETL process. It extract data from several sources, transform it for analytics, and load it into the data warehouse. It operates on a hybrid architecture.

Comparison between AWS and Snowflake 

1. AWS vs Snowflake: Pricing

Pricing of AWS

AWS pricing

1. Free Tier: For new users, it offers a Free Tier for a two-month trial of the DC2.Large node.

2. On-Demand Pricing: In on-demand pricing, rate is based on the previous configuration and is billed only as long as the cluster is live. The typical hourly rate is $0.25 USD for a DC2.Large node.

3. Redshift Serverless Pricing: With this, costs add only on the active data warehouse and are measured by Redshift Processing Units (RPUs).

4. Managed Storage Pricing: It is calculated on a per hour basis as a function of the total amount starting as low as $0.024 USD per GB.

5. Spectrum Pricing: The pricing of Redshift Spectrum for data scanned is $5 USD per terabyte.

6. Concurrency Scaling Pricing: For every 24 hours that your main cluster is live, you acquire a one-hour credit.

7. Reserved Instance Pricing: Pricing for reserved instances can either be paid in three ways

  • Paid all up front
  • Monthly for a year with no up-front charges
  • Partially up front.

Pricing of Snowflakes

Snowflake Pricing

1. Standard

  • Complete SQL data warehouse
  • Secure Data Sharing
  • Premier Support 24×365 service
  • Time Travel
  • Always on enterprise-grade encryption in transit and at rest
  • Customer-dedicated virtual warehouses
  • Federated authentication
  • External functions
  • Snowsight
  • Create your own Data Exchange
  • Snowflake Data Marketplace access

2. Enterprise

  • Multi-cluster warehouses
  • Up to 90 days of time travel
  • Annual rekeying of all encrypted data
  • Materialized views
  • Search optimization service
  • Dynamic data masking
  • External data tokenization

3. Business Critical

  • HIPAA support
  • PCI compliance
  • Tri-Secret Secure uses customer-managed keys
  • AWS + Azure Private Link support
  • Google Cloud Private Service Connect
  • Database failover
  • External Functions

4. Virtual Private Snowflake (VPS)

  • Customer-dedicated virtual servers
  • Customer-dedicated metadata store

AWS vs Snowflake: Features

Features of AWS

1. Massively parallel processing (MPP): Massively parallel processing (MPP) is the distributed design approach in which various processors apply a “divide and conquer” strategy to large data jobs.

2. Automatic Scaling: AWS Redshift lets companies only pay for the used resources and can automatically scale up and down to match shifting workloads.

3. Fully Managed: Amazon Redshift helps companies in handling infrastructure management, maintenance, or backups,

Features of Snowflakes

1. Multi-Cloud Support: It is a cloud-based data warehousing solution, supporting various cloud providers that includes Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). This feature enables you to choose your preferred cloud provider.

2. Support for Streaming Data: It provides support for streaming data, enabling you to investigate and analyze data in real time. This feature can be very useful for businesses that depend on real-time data to make their decisions.

3. Secure Data Storage: Snowflake offers a variety of features including security to ensure that your data is safe and secure. It is SOC 2 Type II certified which means it meets the highest security standards.

AWS vs Snowflake: Benefits

Benefits of AWS

Benefits of AWS

1. Choice of Many: Amazon Redshift has been a choice of many customer and is one of the first technologies in cloud-native data warehousing.

2. Ease of Administration: Amazon Redshift provides variety of tools to decrease the administrative burden involved in running a database.

3. Scalability: The scaling ability is the most essential aspect of a database. Scaling a Redshift cluster is more simple than scaling an on-premises database.

4. Security: Robust identity and access management, SSL connections encryption in transit and at rest, and role-based access control (RBAC), are some security benefits in Redshift.

Benefits of Snowflake

Benefits of Snowflake

1. Data ingestion: It provides a solution with its continuous data ingestion service, Snowpipe.

2. Machine learning: It supports machine learning use cases, allows analysts and data scientists to build, and deploy machine learning models within the Snowflake platform.

3. Data sharing and collaboration: It offers a seamless and secure way for you to share and collaborate your data by Snowflake Marketplace.

4. Business intelligence and analytics: It allows organizations to access insights from their data through advanced analytics and interactive reporting.

Where to use Amazon Redshift?

The AWS data warehouse service fully managed cloud data platform that lets user choose their node types to maximize their data cloud investment. The data warehouse service also supports cloud deployments and on-premises. Moreover, Redshift offers the best price flexibility out of the both services.

Where to use Snowflake?

Snowflake is ideal for workloads with smaller data sets that need minimal latency. Moreover, Snowflake is multi-cloud it means you can use it almost natively across GCP, Azure, and AWS to take benefits of each vendor’s data warehouse strengths and prevent vendor lock-in.


In conclusion, in the race of AWS vs Snowflake both provides best-in-market data warehouse solutions. The choice between both depends on your business needs and resources. For instance, if your business has a low-query workload and needs an scalable, automated, multi-cloud platform, then you can consider Snowflake for you business.

On the contrary, if your organization manages massive workloads on semi-structured data, and structured data then Amazon Redshift is the clear winner.

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