There are many well-known cloud-based data warehousing operating systems to choose from, such as Amazon Redshift, Microsoft Azure, Snowflake, Google BigQuery, and others — as well as many more significant considerations to take into account when choosing the best solution for your company, organization, or business.
While many prominent cloud data platforms provide similar functionality, there are significant variances in cost, scalability, security features, architecture, performance, and other variables.
What is a Data Warehouse?
Nowadays, big data and analytics are becoming the main driving forces behind almost every firm. Over the last decade, the amount of raw data we generate has risen massively. Because of this, data warehouse solutions have had to be created that can effectively manage all inbound and backup data.
Data warehouses are huge repositories of data gathered from various data sources, which are then used by organizations for analytical insights and business information. An effective data warehouse is built on an architecture that provides consistency by collecting data from many operational databases and storing it in a consistent way for easier analysis and faster insights.
A cloud data warehouse, in essence, utilizes the space and computing capacity provided by a cloud provider to combine and store data from various sources for analytical querying and reporting. Data warehouses are now an essential component of harnessing data to acquire deeper business and customer insights.
Data warehouses are essential for gaining deep insights from data. So, the main question now is, which data warehouse is better for your organization? There are many data warehouses to choose from, including Azure Synapse Analytics, Amazon Redshift, Azure Cosmos DB Plus Azure Synapse Analytics, Google BigQuery, and Snowflake. In this article, we’ll look at two of the greatest cloud-based data warehouse options available: Snowflake vs. Amazon Redshift. These easy-to-use and inexpensive services have transformed the speed, volume, and quality of business analytics in modern data warehouses.
Unlock the future of intelligent applications with our cutting-edge Generative AI integration services!
Amazon Redshift vs. Snowflake: The Basics
Redshift
This data warehousing technology enables large-scale data processing and storage by utilizing cloud-based compute nodes. The Redshift tool is completely integrated with the AWS cloud platform and enables a platform for its users where they can store and analyze huge amounts of data to gain business insights.
Amazon Redshift comes ready to be linked with your existing business intelligence tools. All you have to do is ETL or’ extract, transform and load’ your data into the Redshift data warehouse to get going. With Redshift, you have the choice to start off with a few hundred gigabytes and scale up or down later as necessary.
Snowflake
Snowflake is also a cloud-based data warehouse that can be managed or run on AWS, Azure, and GCP. It is primarily different from other data warehousing software as Snowflake is one of the only few data warehouse tools not running on its own personal cloud. Snowflake offers a standard and interchangeable codebase, which allows its users to transport data to different clouds in different areas without any need for re-coding.
It is an analytic warehousing solution for both structured and semi-structured data that operates on a Software-as-a-Service (SaaS) model. Snowflake separates both storage and computing, which allows it to allocate different cloud computing resources for user queries and analytics while having no impact on the data warehouse performance.
Snowflake is extremely quick, adaptable, and user-friendly when compared to typical data warehouses.
So, basically, the similarities are:
- Both tools allow for SQL querying and can be integrated with various Business Intelligence tools and ETL applications.
- They both employ Massively parallel processing or (MPP) architecture and provide quick query processing.
- They both provide scalable, versatile, and secure data storage.
Now, we can look at how Amazon Redshift and Snowflake differ.
Redshift vs. Snowflake: What’s Different?
Pricing
The major distinction between the two is pricing. Their pricing models differ, and depending on your business’s needs, one of these could have an advantage over the other.
As Snowflake’s storage and computing is separate, customers have to pay for these services separately. This allows users a lot more flexibility as you can scale any part of the service at any time according to your requirements.
Redshift, on the other hand, provides both computing and storage as a bundle. This makes their on-demand prices a lot more affordable when compared to Snowflake. Redshift also allows users to scale up or down depending on their needs. Users can also get three-year Reserved Instance pricing to make it more affordable.
Basically, Snowflake is priced per warehouse and how much computing power you need. In contrast, Redshift is priced by the hour and per node you use.
SERVICE DISABLED VETERAN OWNED SMALL BUSINESS (SDVOSB)
Maintenance
Until a few years ago, Snowflake was much easier to maintain than Redshift, as Redshift provided no automated maintenance tools. Now, both Snowflake and Redshift have a number of automated maintenance tools, such as workload management, auto-vacuuming, and more.
Security
Both Amazon Redshift and Snowflake include security features and measures on their services. Redshift maximizes security for all its users, while security on Snowflake varies depending on the tier you purchase.
Redshift offers end-to-end encryption, access management, SSL connections, cluster encryption, and more. Snowflake, on the other hand, offers VPC/VPN for managing security, multi-factor authentication, controlled object security, and more.
Both services also comply with various data protection standards. Redshift is ISO, HIPAA BAA, PCI, and SOC 1,2,3 compliant. Snowflake is also SOC 1 and 2 compliant for all Snowflake editions. Snowflake’s Business Critical Edition or higher are HIPAA, HITRUST, and PCI DSS compliant.
Small Disadvantaged Business
Small Disadvantaged Business (SDB) provides access to specialized skills and capabilities contributing to improved competitiveness and efficiency.
Conclusion
Both Amazon Redshift and Snowflake are two of the best cloud-based data warehouse solutions available today. Both offer huge storage and provide powerful data computing, management, and analysis options.
You can’t go wrong choosing between these two, but your choice should depend on what your business needs and requirements are. Factor in your business resources, demands, and use cases, and make your choice! If your business is already working on AWS or your data collection is already massive, you might prefer Redshift. If your business is fairly new or you are looking for quick processing, Snowflake could be the solution!
Further blogs within this Snowflake vs. Amazon Redshift: Things You Should Know category.