When you’re looking for a data warehouse platform for your business, you will do better with cloud-based warehouse solutions rather than on-premise databases. Two of the best options around are Snowflake and AWS, but you’ll need to explore how they compare considering they have multiple key differences.

Snowflake is a cloud-based data warehouse service that provides security of data through several industry-standard security measures. Organizations using this data warehouse will enjoy the scalability of storage space, data security, and several other benefits. 

Amazon Web Services (AWS) is a cloud-based data warehouse platform that allows users to store and analyze data to make informed business decisions. Rather than making predictions manually, AWS provides a platform to do this fast and efficiently, giving you more time to focus on other areas of your business.

So, what’s the difference between Snowflake and AWS? Let’s look at the differences, pros, and cons between the two platforms to help decide which is best for your business.

Snowflake vs. AWS: A Side-by-Side Comparison

Both platforms have their share of advantages and disadvantages, so it’s essential to evaluate your needs before making a decision. Let’s go over the key considerations to keep in mind.

SnowflakeAWS
What is it?Data warehouse-as-a-service offering that supports both structured and semi-structured dataCloud computing platform that offers users a wide range of services, including storage, networking, computing, and more
Data IntegrationUses built-in features like STREAMSIt is achieved by using tools and technologies like Athena
Data StorageAutomaticManual
Supported Data FormatsStructured and semi-structuredStructured, semi-structured, and unstructured
Year of Conception20122006
MaintenanceLowNeeds constant maintenance
ManagementNo management requiredSome, which may be difficult and time-consuming

Snowflake vs. AWS: 5 Must-Know Facts

  1. While Snowflake and WPS support third-party integrations, Snowflake’s ecosystem and integration are more extensive as it supports ETL and BI tools.
  2. While Snowflake does not require any management, AWS involves tedious management as users are responsible for maintaining the security in the cloud. This requires some data warehousing skills.
  3. Some of AWS’s services are inaccessible to non-U.S. residents. First-time users may also have access to limited resources due to fear of hacking activities. 
  4. As Snowflake gives users fewer choices to customize data, AWS features like data partitioning and distribution allow for enhanced data flexibility.
  5. Snowflake uses a strict security measures protocol, while AWS allows users to choose their security model.

Snowflake: Complete History

Snowflake is a data cloud company founded in 2012 by three experienced data warehousing experts. Two founding members previously worked for Oracle Corporation, while the third co-founded Vectorwise.

The company officially launched to the public in 2014, though its first product wasn’t available until 2015. Despite a slow start, Snowflake has since grown steadily; as of 2020, they have over 3,400 active customers, including big names like Adobe and Capital One.

The company has achieved steady growth, thanks to its outstanding management. It has won several awards, including first place at the 2015 Strata + Hadoop World startup competition and LinkedIn’s 2019 U.S. list of Top Startups, and second place on the Forbes Cloud 100 list. The company became public in 2020 through a highly successful software IPO.

Snowflake data storage management warehouse
Snowflake has many high-profile clients and is growing rapidly.

What is the Future of Snowflake?

Data warehousing has grown to become a business necessity in data science, business intelligence, and SQL analysis. It collects and processes data from multiple sources to make useful business predictions. Snowflake, being a Software-as-a-Service (SaaS), means that it has no physical or software components and runs only on public cloud infrastructure. 

Snowflake allows businesses, departments, and subsidiaries to access data easily and securely. 

With all the good features of Snowflake, it is a high possibility that it will grow to become an industry leader in cloud data warehousing and analytics.

Snowflake vs. AWS: What’s the Difference?

Architecture

Snowflake’s architecture combines the cloud and a structured query language (SQL) engine. Additionally, its architecture combines the typically shared disk and the shared-nothing database design, allowing it to have three primary layers. These layers are query processing, cloud services, and database storage.

As opposed to Snowflake, AWS’s architecture only uses the shared-nothing database. It also features clusters of data warehouses with its compute nodes broken down into node slices. Each node slice is attached to a section of the node’s memory and disk space and helps process part of its workload. The primary node distributes data to the node slices using Java Database Connectivity (JDBC) or Open Database Connectivity (ODBC) standards for effective communication.

Security

Snowflake is the most secure regarding the security measures in Snowflake and AWS.

Snowflake observes several data protection standards, including PCI DSS, HITRUST for Business Critical Edition, and HIPAA. It has further covered several security threats by encrypting all its files and data.

For AWS, data security is taken care of by AWS itself and the users. AWS ensures the cloud is secure, while the users ensure security in the cloud is fine. It also observes various security standards, including HIPAA BAA, ISO, and SOC 1, 2, and 3.

Performance

In the Snowflake data warehouses, compute and storage are not together —  a feature that allows it to process several queries simultaneously without impacting each other. This gives it high-performance speeds. While AWS performs well, it is a bit slow when processing unstructured data. However, you can improve its overall performance by using distribution keys.

Ecosystem and Integration

Ecosystem and integration are crucial factors when assessing the differences between Snowflake and AWS. Snowflake has connectivity with several data integration, business intelligence (BI), and analytics tools, while AWS supports integration with other components in the AWS ecosystem.

AWS Amazon Web Services
Amazon Web Services (AWS) is integrated with all components of the ecosystem, making your data management easy because it’s all in one place.

Pros and Cons of Snowflake vs. AWS

Pros of SnowflakeCons of SnowflakePros of AWSCons of AWS
Observes advanced data security measuresIt experiences lapses during data streamingIts console makes it easy to use and view analytics and queryUsers are limited to a few resources based on their region
You don’t need to install, configure, or manage the data warehouse platformIt’s difficult to migrate large amounts of dataThe system supports many data output formatsIt has several cloud computing issues, like inadequate backup protection
Provides good documentationProvides no opportunity to use on-premise softwareIt is a fully managed platform necessitating little effort to maintain or upgradeBilling for using the platform can be confusing for users
Allows the sharing of data by multiple accountsIts pay-per-use model creates room for hidden costsUsers are guaranteed speed and agility while using AWS applicationsSome of its services may not be available to non-U.S. residents
High integration with several components of the data ecosystemDoes not provide adequate support for unstructured dataOffers a simple and secure method of payment for services usedNo proper handling of unstructured data
No management requiredIts support for stored procedures is not very powerfulSecurity is guaranteed as it complies with several data protection standards
It’s easy to set up and use

Snowflake vs. AWS: Which One Should You Choose?

While both AWS and Snowflake are highly beneficial and well-suited for various applications, Snowflake has the edge over AWS for a few reasons.

Snowflake’s architecture combines cloud and SQL query engine, while AWS only uses nothing-shared databases, giving Snowflake high-performance speed. Similarly, Snowflake enables users to buy only the features they need as opposed to AWS, which allows for scalability.

In addition to being easy to use, a data warehouse must also have tight security measures to protect your company’s information. Fortunately, both industry leaders, Snowflake and AWS, have complied with standard security procedures.

However, Snowflake takes the lead regarding the overall safety of your data. Additionally, users of Snowflake won’t encounter common backup data issues that often come up during the migration process on AWS platforms. Finally, time management is crucial for any business owner; you’ll be thankful to know that several tasks are automated in Snowflake, which streamlines the process, unlike with AWS, where some tasks (data vacuuming and compression) can not be completed without human intervention.

While Snowflake may not be accessible to people outside the U.S., it is still the best data warehousing solution to help grow your business.

Snowflake vs. AWS: How Do They Compare? FAQs (Frequently Asked Questions) 

How does Snowflake differ from AWS?

A significant difference when looking at Snowflake and AWS is that Snowflake’s architecture uses both cloud and SQL engines, while AWS uses nothing-shared disks only.

 

 

Are Snowflake and AWS secure?

Yes, both Snowflake and AWS comply with established data protection measures. Even so, a few loopholes in AWS makes Snowflake more secure.

Is Snowflake built on top of AWS?

Yes, the Snowflake cloud data warehouse is built on AWS infrastructure. It’s a SaaS offering that does not involve installing, configuring, or managing hardware or software.

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Does Snowflake use AWS for storage?

Snowflake’s clever integration and objects allow it to read from Amazon S3 and write on it. To access the files stored on S3, Snowflake will utilize AWS’ Identity and Access Management system.

 

Is Snowflake better than AWS?

Yes. Snowflake has various features that make it stand out and be considered a better data warehouse than AWS.

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