Is Snowflake Data Warehouse better than Amazon Redshift?

Snowflake and Amazon Redshift are two prevalent cloud-based data warehousing platforms that offer excellent performance, business intelligence, and scaling capabilities. 

The amount of raw data generated has grown dramatically in recent years. It has led to the need for data warehouse technology that can smoothly manage all the incoming data. More precisely, the need is for enterprise-level cloud-based technology. Data warehouses have become crucial in leveraging data to gain more in-depth business and customer insights—many big names to choose from, such as Snowflake and AWS Redshift. But which one should you choose?

Keep reading to learn if the Snowflake data warehouse is better than Amazon Redshift. 

You’re already familiar with the snowflake ETL or Redshift ETL similarities if you have ever used both of those services. Both data warehousing systems are effective and equipped with powerful data management features.

Compute and storage are entirely separate when it comes to Snowflake data warehouse , and the storage cost is similar to storing the data on AWS S3. But AWS addressed this problem by introducing Redshift Spectrum, which lets you query data that exists directly on S3, but it is not as efficient as with Snowflake.

Nevertheless, there are a lot of deciding factors to consider regarding which data management warehouse service is right for your business. You’ll need to compare their features, costs, integrations, security, and maintenance to make the correct decision.

Snowflake is an effective and robust cloud-based warehousing database management system. It is based on a Software-as-a-Service (SaaS) model and provides an analytic warehousing service for structured and semi-structured data.

It’s not built as an addition to an already existing software platform. Instead, Snowflake uses a structured query language (SQL) database engine with an architecture mainly designed for the cloud.

Snowflake is extremely fast, flexible, and user-friendly compared to conventional data warehouses.

AWS Redshift

AWS Redshift is a fully managed cloud-based data warehouse service that runs on a petabyte-scale. It is part of a more comprehensive cloud-computing platform run by Amazon Web Services, and it lets you use your data to gain new business and customer insights.

The Redshift data warehouse can be effortlessly integrated with your business intelligence(BI) tools. The service generally starts with a few hundred gigabytes of data, allowing you to scale up or down as required.

To start using Redshift, you have to work with a set of nodes referred to as the Redshift cluster. Once you properly allocate the cluster, you can begin uploading your data sets to run data analysis queries and make better business decisions.

Snowflake and Redshift are pretty similar. However, their differences are pretty significant. To properly compare them, one should look at their integrations, maintenance, security, features, and costs. Consider the following factors before choosing Snowflake or Redshift:

1. Ecosystems and Integrations

Integrating the Redshift data warehouse will be easier if you already work with AWS. Redshift can integrate with various AWS services, including Cloudwatch, Schema Conversion Tools, Kinesis Data Firehose, Glue, EMR, Athena, and SageMaker.

Snowflake also delivers on-demand functions within the AWS marketplace. Nevertheless, it doesn’t have the same integrative functions, making it challenging to use with some of the above-listed tools like Kinesis, Glue, or Athens. But, Snowflake offers some unique integration points such as IBM Cognos, Informatica, Power BI, Tableau, and Apache Spark.

Both Snowflake and Redshift warehousing services come with extensive integrations and reputable ecosystem partners. Regardless, Redshift is much more established than Snowflake and would make your entire data transition much easier if you’re currently working with AWS.

2. Maintenance and Security

The reality of our data-driven world is a vast gap between the amount of data that is being produced and the amount of data being secured. Hence, warehousing security is given the highest importance. With each new piece of data created, new security exposures crop up for sensitive information.

Both warehousing services provide quality security features. Redshift’s database security measures include:

Snowflake also provides a heap of high-level security features, such as site access controlled through an IP, controlled object security, multi-factor authentication, automatically encrypted data security, and security validations that are in compliance with compliance laws.

Redshift doesn’t let you start new data warehouses without copying previous ones when it comes to maintenance. You’ll have to assess the same cluster continually while looking for available resources. However, with Snowflake, computation and storage are separate, making it easier to create new data warehouses of differing sizes. It is perhaps where Snowflake has the upper hand over Redshift.

3. Pricing

One of the most significant differences between AWS Redshift and Snowflake is their pricing models. Redshift is more affordable than Snowflake when it comes to pricing. Redshift also gives a Reserved Instance (RI) model for more extended periods, which offers a subscription type of deal so customers can save money.

Redshift charges per hour and node, while Snowflake charges per warehouse and usage pattern. Snowflake’s pricing model is somewhat confusing as storage is decoupled from their computational warehouses, which means users are charged separately for their data storage and warehousing.

Snowflake offers seven levels of its computational warehouse services, also known as “clusters.” They are based on a dynamic pricing model, which aims for flexibility and resizing, which helps customers save money. However, when you compare the two services based on price, Redshift is a bit more affordable.

Your preference between Snowflake’s data warehouse and AWS Redshift’s data warehouse should be based totally on the specific requirements of your business, your resources, and your budget. If you’re currently working with AWS and your workloads range into the billions, Redshift might be most suitable for your needs. However, if you are looking for speed to move an on-premise data warehouse into the cloud, Snowflake is the best solution.