Snowflake Tutorial

Snowflake Tutorial : A Beginner Guide for Knowing What it is & How it Works

Data has been growing at an alarming rate over the past few years and organizations across the globe are treating data as an important business asset because of the value it holds. Data warehouse platforms enable businesses to access a wide range of data sources using a centralized platform and support business users with the right insights in making effective business decisions. Modern businesses require advanced data warehouse solutions but the traditional data warehousing platforms have failed to cope up with the ever-evolving data needs.

Snowflake is an advanced cloud-based data warehouse platform, natively built for the cloud and offers multiple to meet the data warehousing needs of the modern business world. This Snowflake tutorial has been designed to provide you with complete knowledge of all the essential concepts of the Snowflake data warehouse platform. In this snowflake tutorial, we are going to cover various concepts such as challenges associated with traditional warehouses, what is Snowflake, Snowflake architecture, features, advantages and much more.

Following are the concepts covered in this Snowflake Tutorial:

Table of Contents

Challenges associated with traditional data warehousing platforms:

The traditional data warehouse platforms once satisfied the needs of the organizations but now the scenario has changed. Growing demand for data management and accessibility has become essential but the rigid architecture of traditional data warehouses is unable to scale along with the growing data. When exposed to large volumes of data it has witnessed many challenges.

Following are the major challenges associated with traditional data warehouse platforms:

  • Complex architecture
  • Inflexible structure
  • Outdated technology
  • Slow performance
  • Lack of governance

What is Snowflake?

Snowflake is a cloud-based data storage and analytics service provided as a SaaS. It has transformed the data warehouse industry by making it possible to bring all your business information into a single system that supports all your workloads and users. Snowflake natively built for the cloud and eliminates the issues associated with traditional solutions such as cost, infallibility, and complexity.

Unlike other data warehouses, you are not required to have any additional hardware or software to install, select, configure or manage Snowflake. Snowflake’s advanced data sharing capabilities and innovative architecture have acquired its huge popularity. It supports organizations by simplifying the process to share data in real-time.

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Why Snowflake?

Snowflake is an advanced cloud data warehouse platform and its unique capabilities have set it apart from all other data warehouse platforms. This data warehouse can be built on top of Microsoft Azure cloud or Amazon Web Services infrastructure. You can use it on top of your cloud provider without installing any software and hardware. Snowflake takes care of the tasks such as setup, maintenance and support.

Snowflake architecture makes a big difference from its peers by enabling storage and computation to scale independently. So the customers can pay only for what they use and they can pay separately for storage and computation. Its powerful data sharing capabilities allow organizations to share real-time data in a secured way.

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Snowflake Architecture

Snowflake has come up with an advanced and unique architecture that is a combination of shared-disk and shared-nothing architectures. It uses a central data repository to store data consistently and makes it available to access from all compute nodes in the platform. Similar to shared-nothing architecture, Snowflake also executes queries by using MPP (massively parallel processing) compute clusters where every node in the cluster stores a certain amount of the whole data set locally.

Snowflake architecture simplifies data management with shared-disk architecture and adds performance and scalability advantages with shared-nothing architecture. Snowflake’s unique architecture consists of three layers which are database storage, Query processing, and Cloud services.

Snowflake architecture consists of the following three layers:

  1. Database Storage
  2. Query Processing
  3. Cloud Services

Let’s discuss each Snowflake architecture layer in detail:

Database Storage Layer

Whenever the data gets loaded into Snowflake it arranges the data into optimized, compressed and columnar format. After this process, the data gets optimized and then stored in cloud storage.

Snowflake looks after how the data gets stored which include data organization, compression, structure, file size, statistics, metadata, and many other aspects related to data storage. All the data objects stored in Snowflake are invisible and inaccessible. One can only access the data objects by running SQL query operations using Snowflake.

Query Processing Layer

All the query executions are performed in this processing layer. Snowflake uses “virtual warehouses to process queries. Each virtual warehouse is an MPP (massively parallel processing) compute cluster which consists of multiple nodes allotted by snowflake from a cloud provider.

Each virtual warehouse in the query processing layer is independent and does not share its computational resources with any other virtual warehouses. This makes each virtual warehouse independent and shows no impact on the other virtual warehouses in case of any failover.

Cloud Services Layer

The Cloud Services layer consists of a set of services that coordinates multiple tasks across the Snowflake platform. All these services tie together and work with great co-ordination to process user requests, from login to query dispatch. This layer also executes compute instances assigned by Snowflake from the cloud manager.

Following are the various services managed by this layer:

  • Authentication
  • Metadata management
  • Infrastructure management
  • Access control
  • Optimization and query parsing

Snowflake supported cloud platforms

Snowflake is natively built for the cloud and runs on cloud infrastructure. Snowflake architecture layers (storage, compute, and cloud services) are deployed and managed on the cloud provider.

Following are the cloud platforms supported by Snowflake:

  • Google Cloud Platform
  • Amazon Web Services (AWS)
  • Microsoft Azure (Azure)

Snowflake Key features

Snowflake offers powerful features compared to its peers. Following are some of the notable Snowflake features:

  1. Innovative Snowflake Cloud Architecture

  2. Supports Semi-structured Data JSON/XML

  3. Database and Object Closing

  4. Virtual Compute Warehouse

  5. Snowflake Object Recover

  6. Change Data Capture (CDC).

  7. Continuous Data Protection – Time Travel

  8. Snowflake Caching Results

  9. Auto Optimization

  10. Snowflake Snowpipe

  11. Secure Data Sharing

Snowflake Advantages

Snowflake is a revolution in the Data warehouse industry and disrupted the market with its advanced capabilities. It has come up with the solutions to handle new data querying needs and eliminated roadblocks associated with traditional offerings.

Following are the top benefits of Snowflake:

High Performance and Speed

Snowflake allows its users to run high volumes of queries or load data faster. You can do it by scaling up the virtual warehouses to use the extra computational resources available. Later you can scale down the virtual resources which you have scaled up and pay for the only time you have used.

Supports Structured and Unstructured Data Storage

Snowflake is highly flexible and allows users to combine structured and unstructured data for analytics purposes. You can directly load data into a cloud data warehouse without needing to transform the data into a relational schema. Snowflake’s advanced mechanism allows you to automatically optimize data querying and storage processes.

Concurrency and Accessibility

Concurrency (Executing multiple queries at a time) is the main issue with traditional warehouses. With traditional offerings, the chances are higher for failover or delay when many queries are competing for resources.

Snowflake architecture has been designed in an innovative way in order to address these concurrency issues.  All the virtual warehouses in the snowflake are independent and do not affect the performance of other virtual warehouses which helps you easily scale up or down based on the requirement. The users can get the information at a lightning speed without any need to wait for loading and processing.

Simplified Data Sharing

Data sharing involves a bit complex process when using traditional data warehouses but this is not the case with the Snowflake. Snowflake advanced architecture allows you to create a reader account that enables seamless data sharing options between the snowflake users and external parties.

Availability and Security

High availability is one of the essential benefits of the Snowflake data warehouse platform. It can be distributed across all the regions of the cloud provider. It has been designed in a way to deliver constant services and shows little impact even when there are component or network failovers. It also offers advanced security measures by using SOC2 type II and more extra standard features.

Snowflake vs Redshift

Snowflake and Redshift are powerful data warehouse platforms and come with unique features to full-fill the data warehouse needs of the organizations.

let’s understand the core differences between the Snowflake and Redshift.

Redshift: It is a cloud-based data warehouse platform that allows organizations to start even with a few hundreds of gigabytes of data and allows them to easily scale petabytes and more. It uses columnar data storage technology and to provide high querying performance to the users.

Snowflake: Snowflake is a cloud-based data storage and analytics service provided as a SaaS. It has transformed the data warehouse industry by making it possible to bring all your business information into a single system that supports all your workloads and users.

The following table gives you a clear difference between Snowflake and Redshift.



It works pay as you go, model

Great discounts on long-term

Robust JSON based functions

Falls bit a short for fast query support compared to Snowflake

High-speed scaling

It takes a few minutes to add more nodes

Unique architecture

The advanced Machine learning engine

Fully Automatic

Manual intervention is needed

Closing Thoughts

Data warehousing platforms play a vital role in these data-driven business worlds. Snowflake has disrupted the entire data warehouse industry with its unmatched features. Corporations across the globe have started implementing snowflake and there is a great demand for certified Snowflake professionals. Hope this Snowflake tutorial for beginners helped you with some useful information. If you are about to start your career as a Snowflake developer and looking for the right information to clear your Snowflake interview then check out our Snowflake interview questions. Happily learning!

Author Bio


Yamuna Karumuri is a content writer at CourseDrill. Her passion lies in writing articles on the IT platforms including Machine learning, Workday, Sailpoint, Data Science, Artificial Intelligence, Selenium, MSBI, and so on. You can connect with her via LinkedIn.

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