Data driven intelligence is one of the major aspect to strengthen successful latest businesses. Most companies consider high quality cloud data warehouses to store their operational data while allowing business intelligence data analysis and activities.
Undoubtedly, AWS Snowflake and Amazon Redshift are the superior in class cloud based data warehouse solutions. These cost effective and user friendly services have transformed the volume, acceleration and quality of the business analytics in the advanced data warehouses.
Even though, both solutions are among the top list in the market, it can be tricky to select the one over another. It is not the case of the high quality solution, but instead, which one is better for the data strategy.
Let’s find out the differences points between AWS Snowflake and Amazon Redshift and its comparison while considering the choosing the latest data warehouse.
AWS Snowflake And Redshift Fundamentals
When we talk about cloud-native data warehouses we cannot miss the two major and popular cloud-based data warehouses known as AWS Snowflakes and Redshift. They are known for their excellent data management and are popular for the exciting options that they offer.
In this article, we will discuss AWS Snowflake and Amazon redshift. We will also review their common features and the pros and cons of each.
So without wasting time let’s proceed.
AWS Snowflake
The AWS Snowflake data warehouse is a data warehouse that provides analytical insights or unstructured and structured data. It is an easy-to-use SaaS solution, capable of separating storage and computing. It offers modern data architecture with the least downtime and maximum flexibility. It is a partner of AWS.
By using a concept known as a virtual warehouse, AWS Snowflakes are fast, easy, and very flexible. The virtual warehouse used by AWS Snowflake, allows you to make several data warehouses on the same data. Along with this virtual warehouse concept, AWS Snowflake also uses a query service layer for management, optimization, and security of data. It means that by using this setup you can run multiple at the same time with speed and simply not affect the functioning of each other.
It is responsible for delivering the Data Cloud which is a global network having thousands of organizations and their mobilized data of unlimited scale, performance, and concurrency. It is best known for its automated maintenance.
Amazon Redshift
Amazon Redshift is a fully managed and well-maintained data warehouse. It helps organizations and businesses in storing and analyzing huge amounts of data. Besides that, it has the ability to co-exist with on-premises infrastructure and it can also integrate with other services of AWS. It is capable of providing enhanced security to your data. It has a straightforward and clear pricing model. Amazon Redshift is known for its dependable options for backup and multiple output formats for data.
One of the most prominent features of Amazon Redshift is Amazon Redshift Spectrum. This is a very desirable feature as it offers fast data analysis and allows its users to perform SQL queries directly on the stored data. It is also capable of supporting semi-structured data types like JSON. It can also integrate itself data ecosystem of AWS. It enables you to build ETL pipelines for loading and processing data. Furthermore, it also allows streaming of data ingestion and optimization of queries.
Amazon Redshift has a shared-nothing architecture where every compute node is having a separate memory, disk space, and CPU. It is accessible through SQL querying and both of them are capable of integrating with business intelligence (BI) tools and third-party ETL. It is more suitable for workloads demanding high performance as compared to AWS Snowflake. It also allows its users to leverage intelligence tools of other businesses as well.
Common Features
As both the AWS Snowflake and Amazon Redshift are data warehouses, so they both have some features in common. Their common features are
- They both are accessible through SQL querying and both of them are capable of integrating with business intelligence (BI) tools and third-party ETL.
- Both of them provide fast query execution.
- They both are used for the security of the stored data.
- They both have flexible nature.
Key Differences
Since we have discussed the common features of both the data warehouse, let’s discuss the differences between the features of both warehouses.
Performance
One should know that AWS Snowflake and Amazon Redshift are two data warehouses that are using different architectures for functioning. This shows their different behaviors that distinguish them from each other. So it can be a little tough and tricky to compare their performance.
They have different un-optimized query run times. And we can say that AWS Snowflake has a better un-optimized query performance. AWS Snowflake also offers congruent scaling like Amazon Redshift, but it cannot provide machine learning capabilities as offered by Amazon Redshift. AWS Snowflake’s initial query time is lesser than Amazon Redshift. While Amazon Redshift provides several ways for standardizing data structure and queries.
Maintenance
Now if compare the maintenance of both the data warehouses, Amazon Redshift requires manual housekeeping while AWS Snowflake is fully automated. This is one of the reasons why AWS Snowflake is usually preferred over Amazon redshift as Amazon Redshift does not offer fully automated maintenance like AWS Snowflake.
This feature of AWS Snowflake creates a gap between the two data warehouses. But Amazon Redshift is trying to overcome this gap by introducing its auto vacuuming and auto workload management (WLM) feature.
Ecosystem and Integration
Now, we can also differentiate the two data warehouses on the bases of their ecosystem and integration. Although, both Amazon Redshift and AWS Snowflake offer their support for third-party integrations, Amazon Redshift provides increased support for third-party integrations and has an extensive ecosystem as compared to the ecosystem of AWS Snowflake.
Pricing
As far as pricing is compared, both Amazon Redshift and AWS Snowflake have different pricing structures. If we talk about AWS Snowflake, it can be referred to as pay-as-you-use. However, predicting the actual cost is quite a tricky task. And in some cases, AWS Snowflake gets quite expensive to use because of its seven-tier pricing system.
Now if we talk about the pricing scheme of Amazon Redshift, as compared to AWS Snowflake it is quite simple and transparent. It is easy to predict the total cost of the Amazon Redshift. There is a simple formula for determining the monthly cost for Amazon Redshift, we can calculate the monthly cost of Amazon Redshift by using the formula mentioned below
Amazon Redshift Monthly Cost = [Price Per Hour] x [Cluster Size] x [Hours per Month]
Security
We can also differentiate the two data warehouses on the bases of the security that they provide to their users. We can see that Amazon Redshift provides a higher degree of security as compared to AWS Snowflake which has a jagged approach. AWS Snowflake provides encryption along with VPC/VPN network isolation. But its security is dependent on the version you are using and it may cause you additional costs. While Amazon Redshift offers end-to-end encryption that fits your security demands and it does not cause any extra cost.
Storage and Compute Separation
AWS Snowflake allows its users to scale services accordingly as it separates the compute from storage. This is a feature that is not offered by Amazon Redshift and previously it had no physical separation between the two processes that are storage and computing. But now it has introduced this feature and provides a similar environment to AWS Snowflake by the introduction of R3 nodes.
Pros And Cons
Once we have done the comparison of the features of both the data warehouses, let’s move on to the pros and cons of each data warehouse.
AWS Snowflake Pros
The pros of AWS Snowflake are mentioned below
- It is an easy-to-use SaaS solution.
- It is capable of separating storage and compute
- It offers its users automated maintenance.
- It is also capable of supporting semi-structured data types like JSON.
AWS Snowflake Cons
The cons of AWS Snowflake are mentioned below
- As it is operating on the cloud it does not support the on-premises infrastructure.
- In most cases, it is more expensive than the Amazon Redshift.
- The extent of security is dependent on the type or product version you are using, which further increases the costs
Amazon Redshift Pros
After discussing the pros and cons of AWS Snowflake, now let’s discuss the pros and cons of Amazon Redshift.
Following are the pros of Amazon Redshift.
- It has the ability to co-exist with on-premises infrastructure and it can also integrate with other services of AWS.
- It has a straightforward and clear pricing model.
- It is capable of providing enhanced security to your data.
- It also provides dependable options for backup.
- It offers multiple output formats for data.
- It is efficient in the execution of queries and analysis.
Amazon Redshift Cons
Following are the cons of Amazon Redshift.
- One of the cons of Amazon Redshift is that it is quite costly and may cause extra costs.
- Another con is that though it is offering two release cycles that are the Current Maintenance Track and Trailing Maintenance Track but in actuality, it is limited to the Current Maintenance Track only.
Conclusion
So after reading this paper, we hope that you get the concept of AWS Snowflake and Amazon Redshift. We have also highlighted their common features and differences. In the end, we also mentioned the pros and cons of each data warehouse for your better understanding. Hope this article is helpful in enlightening your knowledge regarding each data warehouse.
