The on-premise MS SQL Server database has been around since 1989, helping companies store and process data. However, it comes with its limitations. As your data increases exponentially, you have to scale up your storage & compute resources. That too economically without any compromise on the performance. That’s where cloud-based data warehousing solutions like Snowflake steps in.
But how do Snowflake vs SQL Server compare? Each has its pros and cons and is beneficial based on different use cases. No sweat! We have compiled a comprehensive list of differences for you. In 7 nifty minutes, you can decide on the best data storage solution for your business.
Snowflake vs SQL Server Analysis
MS SQL Server traditionally has been used for transactional data entry use cases such as eCommerce, banking, website traffic, etc. Hence, if your intention is not to build a data warehouse and keep all your data on-premise, then Snowflake might not be the best choice. However, if you are looking for a cloud-based solution that can take in data from multiple cloud applications, then Snowflake can be that platform. Though SQL Server can also be hosted on Azure cloud, this article is focused on the most common use case.
Before choosing between Snowflake vs SQL Server for your data storage needs, it is always a good practice to consider and investigate all the following factors:
1. Snowflake vs SQL Server: Performance
The rapidly increasing data in business activities is one of the core reasons you would wanna switch from SQL Server to Snowflake. The moment you realize you are pushing through a lot more data to your SQL Server system than it can handle, you will have to add more resources. Buying that extra equipment for just a once-in-a-month peak load that sits idle for the rest of the time is not economical.
This is where Snowflake actually shines! You can get up and running in no time with Snowflake. Need more compute & storage power on the fly? Let Snowflake do it for you instantly, or select a warehouse size based on your requirement. It provides on-demand scaling up or down according to your consumption needs with a consistent stellar performance. You can directly focus on analyzing data rather than worrying about warehouse infrastructure. With Snowflake, you can allocate separate compute nodes for all the different groups using the data warehouse. Then they can each independently query the same datasets without stepping on each other’s toes.
However, Snowflake’s zero management idea also means limited options for you to custom-tune your performance. You will either go for clustering on a column, scaling up the compute, or rewriting your query and splitting it up to dump intermediate results in tables. SQL Server’s indexing can easily get this job done.
2. Snowflake vs SQL Server: Cost
Unlike conventional subscription-based models, Snowflake charges you for only what you use. For the data storage, you have to pay according to the number of bytes stored in a month. Whereas for compute consumption, Snowflake charges on the number of credits used to run queries. This, again, depends on the type of Snowflake plan you have selected and the size of the virtual warehouse you use.
When comparing Snowflake vs SQL Server, you have to only pay for the licensing costs for the SQL Server. However, this also includes server costs( electricity, cooling system, etc.), trained personnel to operate the system, and good network infrastructure. You will also be paying timely maintenance costs and always have a good budget to buy new infrastructure in case you need to scale up.
Hence, for data warehousing, Snowflake tends to be a more economical choice as you don’t worry about purchasing new equipment for scaling up or maintaining the whole server system.
3. Snowflake vs SQL Server: Control
Opting to remain with an on-premise database engine could be due to your company’s data policies or any other reason. This has its benefits. SQL Server gives you complete control over the database backup schedule, high data availability and disaster recovery, encryption used, amount of logging, etc.
With the Enterprise Edition, Snowflake assures total data security with customer-managed encryption keys and has HIPAA and PCI compliance. At any point in time, you can quickly get a bird’s eye of your warehouse operations. For instance, consider the following questions you might have:
- Who’s running what queries and when?
- What pipelines are eating up the most computing power?
- When was the last time a specific user logged in?
- How has the data warehouse size changed over time?
- How did the data in this table look a couple of days ago before that latest set of changes?
- What was that one useful query you ran yesterday but forgot to save?
The intuitive UI allows you to instantly answer all these questions without anyone’s assistance. You can always monitor your resource usage and stay on top of your budget with Snowflake’s cost-control features.
Summing It All Together
At last, all your doubts have vanished into thin air, and you now know how to select a solution for your business when comparing Snowflake vs SQL Server. Considering your data regulations, budget, performance requirements, and business use case, you can choose the most optimal product. Whichever is your choice, you still have one river to cross! To build a single source of truth for your business, you still need to bring in data from multiple applications and databases.
For building new data connectors and maintaining custom data pipelines, your engineering team will spend 40-60% of their bandwidth. They have to always be on the lookout for any data leakage and fix it when needed. Or, you could try out cloud-based No-Code ETL solutions like Hevo Data that completely automates your data integration process.
Visit our Website to Explore Hevo
With 150+ plug-and-play integrations, you can get your data replication started in just a few clicks. No need to go to SQL Server or Snowflake for your post-load transformations. You can run complex SQL transformations from the comfort of Hevo’s interface and get your data in the final analysis-ready form.
Want to take Hevo for a spin? Sign Up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.
Sanchit Agarwal is an Engineer turned Data Analyst with a passion for data, software architecture and AI. He leverages his diverse technical background and 2+ years of experience to write content. He has penned over 200 articles on data integration and infrastructures, driven by a desire to empower data practitioners with practical solutions for their everyday challenges.
