Snowflake vs SQL Server 101: The best solution for you!

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.

4. Snowflake Vs SQL Server: Security

Determined by security, it is what makes Snowflake and SQL Server vary. Snowflake offers end-to-end encryption so that all data will be encrypted, whether resting or transiting. It also implements various standards like HIPAA, PCI DSS, and SOC 2, making it perfect for those enterprises that deal with sensitive information. The security controls included in Snowflake include customer-managed keys for advanced control and role-based access control (RBAC).

SQL Server allows full control of your security environment. You can set up any encryption standards, TDE, dynamic data masking, and Always Encrypted for better security controls. This enables organizations with strict security controls that require regulating their encryption and compliance standards.

5. Snowflake vs SQL Server: Data Sharing

The feature that distinguishes it is known as Secure Data Sharing. You can share live real-time data across accounts without any copies or movement of data. This in turn facilitates the efficient and secure collaboration between organizations and their external partners. It streamlines data sharing across different regions with compliance boundaries confining data to its predefined area.

SQL Server has no inherent data-sharing capability, as in the case of Snowflake’s Secure Data Sharing, and sharing data forces you to create database copies or export data to external systems-adding complexity and delay.

6. Snowflake vs SQL Server: Automation

Snowflake has automation features  where it includes auto-scaling and auto-suspend/resume for warehouses; only resources used will be consumed with an increase in demand on peak periods. The company uses auto-scaling upwards during uptrend times and downsizes or pauses when not in use; this usually ensures cost-effectiveness, with performance still within the optimal level without human intervention.

SQL Server is so hands-on, especially when it comes to scaling and optimizing resources. SQL Server offers Auto-Growth on database files, but auto-scaling is not provided; therefore, you’d have to keep a closer eye on resource utilization.

7. Snowflake vs SQL Server: Backup and Recovery

For instance, the feature of Snowflake called Time Travel lets users view and restore historical data pertaining to any given period up to 90 days. It is very valuable for recovering data or doing auditing. Further, Fail-safe ensures that deleted data can be recovered for an extra period if the Time Travel expires.

SQL Server also has very good backup and recovery capabilities, including point-in-time restore, full, differential, and transaction log backups. These operations need to be configured and are usually administered manually, unlike Snowflake, where this kind of work is done inside the tool.

Quick Comparison

Features	Snowflake	SQL Server
Performance	Auto-scaling, on-demand compute, and storage. Excellent for large datasets.	Requires manual performance tuning and scaling for large datasets.
Cost	Pay-per-use model for compute and storage.	Licensing fees, infrastructure, and maintenance costs.
Control	Less control, automated management.	Full control over infrastructure, security, and backups.
Data Sharing	Secure Data Sharing across accounts without data duplication.	No built-in data sharing feature.
Backup &Recovery	Automatic backups with Time Travel and Fail-safe options.	Manual backups and recovery, point-in-time restore available.

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.

Want to take Hevo for a spin? Try Hevo’s 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

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