Snowflake Data Warehouse: A Tutorial

Here’s what you need to know about this much-touted cloud platform.

Written by Ben Herzberg
Snowflake Data Warehouse: A Tutorial
Image: Shutterstock / Built In
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UPDATED BY
Brennan Whitfield | Dec 19, 2023

Snowflake is an analytics and data integration platform that many data professionals love. It makes big promises as an independent data warehouse providing fast insights.

What Is a Snowflake Data Warehouse?

Snowflake data warehouse is a cloud-native SaaS data platform that removes the need to set up data marts, data lakes, and external data warehouses, all while enabling secure data sharing capabilities. It is a cloud warehouse that can support multi-cloud environments and is built on top of Google Cloud, Microsoft Azure and Amazon Web Services.

Does it deliver, or is it all marketing hype? What is behind all the marketing talk, and how does Snowflake work in practice? Is there real value behind its fast growth in user numbers? We’ll answer these questions in this tutorial.

Read More About Cloud ComputingWhat Is Cloud Computing? How the Cloud Works

 

What Is Snowflake?

Snowflake is a scalable, cloud-based data warehouse used for data storage, processing and data analytics. The whole data warehouse is built on top of Google Cloud, Microsoft Azure and Amazon Web Services, and can support multi-cloud environments.

Snowflake acts as a SaaS data cloud platform and is fully self-managed, removing the need to set up data marts, data lakes and data warehouses while enabling secure data-sharing capabilities.

With this platform, companies don’t have to install software or hardware, configure it or maintain it. Everything is usable right out of the box.

What Is Snowflake? Here’s a YouTube tutorial. Credit: Snowflake/YouTube

 

How Does Snowflake Work? 

Snowflake utilizes virtual compute instances — virtual machines hosted on computing infrastructure — for data processing and compute tasks. It also uses cloud blob (Binary Large Object) storage to manage the storage of data in its system. Additionally, Snowflake’s data warehouse runs entirely on public cloud infrastructure and doesn’t utilize any physical or virtual hardware.

 

Snowflake Data Warehouse Architecture

Snowflake’s architecture is made up of three core layers:
 

Data Storage Layer

Snowflake offers databases where organizations can easily store semi-structured and structured data sets as well as store and process unstructured data. It automatically manages the data storage process, including statics, compression, file size, metadata, structure and data organization.

 

Query Processing (Compute) Layer

Snowflake requests to analyze data using data warehouses, which is Snowflake’s term for the compute units. That is possible because the compute layer consists of virtual cloud warehouses operating independently as separate clusters. This prevents warehouses from conflicting over computing resources, ensures stable performance and also provides workload concurrency. 

 

Cloud Services (Client) Layer

Snowflake’s cloud services work on ANSI SQL, allowing users to manage data infrastructure and optimize data. Snowflake’s stored data is encrypted and secured in transit and at rest. The platform’s warehousing certifications include HIPAA and PCI DSS.

RelatedAzure Synapse vs. Snowflake: Which MPP Platform Is Right for You?

 

What Are Snowflake’s Benefits?

Here’s how Snowflake’s architecture transforms into practical benefits for data storage and data management.
 

FAST TIME-TO-VALUE 

Snowflake is a complete SaaS platform, which means it requires no installation, setting up or configuration. You can start using the platform with all its features as soon as you subscribe to the service. 

SaaS solutions don’t require ongoing maintenance, as your vendor takes care of everything. There’s no need to hire a dedicated IT team to maintain your solution or train your employees to do this independently. 

 

MULTI-CLOUD SUPPORT 

A multi-cloud environment can prevent vendor lock-in while making the most out of each service. Multi-cloud support lets you rely on Google (GCP), Microsoft Azure and Amazon AWS. For example, one of the platforms might give you better analytics features, while another might be better for boosting security.  

 

STORAGE AND EXPENSE CONTROL 

Because most platforms are interconnected, users have to pay for more storage when they need more compute. Snowflake’s storage and compute are completely separate, and there are no extra charges related to scalability.

 

SCALABILITY, PERFORMANCE AND SPEED  

Snowflake’s multi-cluster architecture removes all concurrency issues. One virtual warehouse’s performance can’t affect the queries of other virtual warehouses. At the same time, every warehouse can scale quickly according to current needs. 

Snowflake supports an unlimited number of concurrent workloads and users. The engine powers analytics processes, feature engineering, interactive applications and complex data pipelines. 

Snowflake’s scalability, performance and speed reduce some of the most apparent data management costs

 

COMPREHENSIVE AUTOMATION 

Snowflake enables companies to automate data resiliency, availability, data governance, security and data management. 

Automation allows companies to handle higher workloads and volumes of data, improving scalability while keeping costs at the same level. It also reduces downtime as companies are always available and can finish processes on time. 

 

EASY DATA SHARING 

Snowflake provides seamless data sharing, cross-region communication and cross-cloud capabilities without the need to use data silos or ETL processes, which are more complex and require more compute resources. 

Anyone can access data through the cloud with seamless compliance and governance policies. When a single data source is shared across the whole enterprise, everyone can be sure they have the latest data, making decision-making and collaboration more effective. 

 

MANY INTEGRATIONS 

Snowflake has an extensive data marketplace of third-party apps and data. This allows teams to connect with their customers with new applications and comprehensive workflows. Regardless of your data pipelines, you can set them in place with these integrations and automate workflows throughout the organization. 

 

What Are Snowflake’s Drawbacks?

Snowflake isn’t perfect. Like any other platform, it has its set of drawbacks worth considering.
 

PAY-AS-YOU-GO MODEL 

Snowflake has no data limits on storage and computing. While that is a great thing overall, Snowflake has a pay-as-you-go model, which means users need to control their data usage to avoid expensive monthly bills. 

 

HIGHER COSTS 

Depending on the applications and use, Snowflake can be expensive compared to its competitors, for instance Redshift. Snowflake bills for one minute each time you start or resume a warehouse and charges for every second after that. 

 

CAN’T BE USED ON-PREMISES 

Snowflake is an exclusive cloud platform, and all its service components, including data storage and compute, run in the cloud. Companies that want to use their solutions on-premises can’t deploy Snowflake.

 

How Do You Start Snowflake?

Here’s how to connect and load data into the platform.
 

SIGNING UP

Go to Snowflake’s sign-up page and enter all the required information, including your name, email and company name. Users without a company can enter any random name in that field. 

After choosing your location, select the Snowflake edition and one of the three cloud platforms you can use.

Click on the link in the verification email you receive to activate the account. Once you do that, enter your username and password, and you can log into your account. All Snowflake editions have a 30-day free trial. 

 

SNOWFLAKE INTERFACE 

Logging into your Snowflake account will direct you to the main interface. The user menu is in the top-left corner of the main window, where you can make changes to your profile, log out, get documentation or switch rules. 

The navigational menu is beneath it. That’s where you can access other pages such as data, dashboards, activity, admin, marketplace and Worksheets. The large area on the right side of the screen is the content pane, where all the elements in the menu you choose are visible.

 

LOADING DATA INTO SNOWFLAKE 

Using the web interface and its loading wizard is the simplest way to load data into Snowflake. Click the Load Data button and choose the location from which you want to load your data. 

The wizard combines data loading and staging phases in one swift operation while deleting staged fields automatically after the process has finished. This approach is only suitable for loading datasets up to 50 MB. 

Further Reading on Cloud ComputingWhat Is Edge Computing?

 

Should You Try Snowflake?

Migrating your data to Snowflake enables you to encrypt and secure it thoroughly, with various specifications, and the interface is fairly intuitive and easy to master. 

Another benefit is that Snowflake’s warehouse processes queries efficiently due to its multi-cluster architecture, helping you avoid concurrency issues. It offers numerous integrations and a multi-cloud environment that allows you to use multiple platforms. Finally, the service is scalable.  

While it is only available as a cloud-based service and the pay-as-you-go pricing can make it more expensive in the long run than some other options, users still get a great deal of functionality for the money.

 

Frequently Asked Questions

Snowflake is a cloud-based data warehouse used to store, process and analyze data. It runs completely on cloud infrastructure and doesn't utilize any physical or virtual hardware.

A snowflake warehouse is made up of database architectures and utilizes database tables to store all data. It also utilizes MPP (massively parallel processing) compute clusters to process queries for the stored data.

A database by itself is an electronically stored and structured collection of data.

Snowflake is a data warehouse platform.

ETL (extract, transform and load) is the process of combining multiple data sources into a single data repository, oftentimes a data warehouse.

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