Complete Guide to Snowflake Multi-Clustered Data Architecture

Summary: The article gives an in-depth understanding of Snowflake and its architecture while explaining how it stores and manages a large volume of data. Also, it provides an overview of the Snowflake functionality and why we need a hybrid version of traditional data warehousing platforms.

Snowflake is a single, integrated, pure cloud-based data warehouse solution provided as Software-as-a-Service (SaaS). It is an analytic data warehouse that is faster, flexible, and easier to use. Moreover, it uses a new SQL database engine and facilitates unique architecture developed exclusively for Cloud.

It is an ideal SaaS solution that allows businesses to focus more on expansion as there is no hardware component for you to select, install, configure, or manage. Moreover, there is no software, and you do not require additional efforts for consistent maintenance, tuning, and management. Everything, including hardware, software, and infrastructure itself, is maintained and managed by Snowflake.

Snowflake physically separates but logically combines compute, storage, and services that make it fairly easy to expand and Contract these elements for scalability. Snowflake Development Platform integrates high performance, agility, simplicity, high concurrency, and higher affordability that other data warehouses lack.

Snowflake doesn’t support private Cloud infrastructures such as on-premises or hosted. It uses virtual compute resources for accomplishing its computing requirements and storage service for uninterrupted data storage.

What is the Need for A Self-Managing System?

-Because data is becoming more diverse and is used differently by organizations. However, a lot of factors make Snowflake a much-needed platform.

Minimal, Easy Administration

Conventional data warehouses demand consistent care and rely upon skilled and experienced administrators to maintain the data platform. The administrators are responsible for choosing data distribution schemas, updating metadata, cleaning up files, creating and maintaining indices, and more.

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Well-Organized & Managed Platform:

The Snowflake data warehouse was designed to eliminate the management of infrastructure. It transparently manages the platform it is built on. Users only require to login to Snowflake services for accessing the platform. The service is available immediately to the users without any complicated setup requirements.

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Handles Capacity Planning:

Users are not required to manage upgrades, patches, or system security as Snowflake looks after the ongoing management of application infrastructure. Since it is essential to scale-up and scale-down the resources as per the business’s growing demands, capacity planning tasks are managed and maintained by the Snowflake only.

Seamless Data Sharing

Snowflake simplifies data sharing, particularly between organizations. Snowflake Data Sharing feature allows one user to allow access to its data to another user. However, it also allows setting up role-based access and detailed permissions to any particular set of data to ensure that the business-critical information is shared with authorized people only.

Understanding SnowFlake Architecture

Snowflake’s multi-cluster data architecture is a hybrid version of the traditional shared-nothing database and shared disk database architectures. You must be thinking HOW; RIGHT?

Snowflake uses a centralized data repository for the collective storage of high-volume data to ensure high accessibility and availability from all computing nodes across the network. That’s how it simplifies data management to that of shared-disk architecture.

Well, Snowflake executes and processes queries massively parallel processing (MPP) compute clusters. In this Cloud architecture, each node in the cluster stores a significant portion of data from the entire data set locally. This is how Snowflake architecture provides scalability and performance benefits of the shared-nothing architecture.

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Snowflake architecture comprises of three fundamental layers that include:

  • Database Storage
  • Query Processing
  • Cloud Services

Database Storage

When a chunk of data is loaded into Snowflake, it reorganizes the data into columnar, compressed, optimized formats in the Cloud. Snowflake takes charge of all the functions that it performs on the data, right from its organization, structuring, compressions, file size optimization, metadata, etc.

Users cannot access the data components stored by Snowflake directly; however, this data is accessible to users through SQL Query functions.

Query Processing

Query processing is a critical function of the processing layer of the Snowflake architecture. It uses virtual warehouses for query processing. Each virtual warehouse is considered massively parallel processing compute cluster of multiple computing nodes that are comprehensively allocated by Snowflake from the Cloud service provider.

Are you new to the term – ‘virtual warehouse’? Virtual Warehouse is a cluster of computing resources inside Snowflake. Its function is to provide resources such as storage, memory, and CPU for performing tasks like SQL execution and DML operation.

Benefits of A Virtual Warehouse

Virtual warehousing brings along multiple benefits that include:

  • You can auto-scale a Virtual warehouse with a minimum or maximum cluster size.
  • It enables the administrators to start or stop the warehouse operations and scale up or scale down without affecting the running processes.
  • Additionally, the user can select to set an auto-suspend or auto-resume virtual warehouse to automatically suspend operations after a period of inactivity. Alternatively, it resumes automatically on the submission of a query.

Cloud Services

The collection of services that coordinates all the functions and activities in Snowflake is termed as the Cloud service layer. The services combine different components of Snowflake for processing user requests effectively from login to the query dispatch. Cloud service layer runs over compute instances provided by Snowflake from the Cloud service provider.


There are other services that the Cloud Service layer incorporates, such as:

  • Authentication
  • Infrastructure management
  • Metadata management
  • Query parsing and optimization
  • Access control

Simply put, Snowflake is designed to deliver the powerful benefits of data warehousing, the agility of the big data solutions platform, and the flexibility f the Cloud. It’s undoubtedly an affordable, easy to implement, zero maintenance infrastructure that brings along dozens of outstanding benefits.

Snowflake architecture is quite simple, and the best thing is that it works on SQL that most IT teams are already familiar with. It cut down the need to learn new technology and hire people familiar with the new system.

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