What is Snowflake Database? Process, Features & Use Cases

What if we told you that you could safely keep all your business data (sales numbers, marketing efforts, customer feedback, etc) with you at all times? Large organizations using the cloud can store and extract their data without getting into the nitty-gritty of tech details. How, you ask? Snowflake database is the answer to everything!

With a market share of about 32.7%, Snowflake is among the best in the data warehousing category. Cloud-based warehousing has inherent advantages and transformative powers, which make this platform capable of changing your growth trajectory.

If you want an answer to ‘what is Snowflake database?’, then this blog is just what you need! Read on for its crucial aspects—architecture, features, benefits, and use cases.

What is Snowflake Database?

Snowflake database is a SaaS, cloud-native data warehousing platform with a unique architecture categorized into separate compute and storage spaces. Modern enterprises use Snowflake’s unparalleled scalability, ease of use, and elasticity to revolutionize data analytics, processing, and storage. It also simplifies data engineering, lakes, science, and warehousing.

The platform works great for modern cloud engineering challenges, especially since it comes without the complexities associated with traditional data warehouses (DWHs).

Let’s first understand how Snowflake stands out from traditional DWHs.

Snowflake Database vs Traditional Data Warehouses

The primary reason behind the rise of the Snowflake data platform is the increasing limitations of traditional data warehouses.

Here is a peek into Snowflake database vs traditional data warehouses:

FEATURE	SNOWFLAKE DATABASE	TRADITIONAL DATA WAREHOUSES
Cloud Native	Built specifically for the cloud.	Usually has on-premises solutions that are adapted for the cloud.
Architecture	Separate compute and storage.	Well-knit with integrated compute and storage.
Data Handling	Provides native support for both structured and semi-structured data.	Works best with structured data.
Scalability	Independent and elastic scaling (size expansion or contraction) of storage and compute without downtime.	Complicated, time-consuming, and expensive; Usually needs over-provisioning.
Cost Model	Pay-as-you-go model for cost optimization as per actual usage.	Requires a high upfront capital expenditure and ongoing maintenance costs.

How Does Snowflake Work?

Snowflake has brought about an extensive change in the way companies manage and analyze large volumes of data. What makes this change possible?

This revolution, often facilitated by expert Snowflake development services, is made possible by its distinctive features and unique operational mechanics.

Depiction of the layers of Snowflake architecture

Let’s understand Snowflake architecture, its resource management, prowess to handle semi-structured data, and scalability. These aspects offer a closer examination of how Snowflake operates.

1. Snowflake Architecture

Its architecture is at the core of the working process. It has three primary layers, each serving a distinct purpose while functioning smoothly.

Storage Layer

It uses scalable cloud storage services to replicate, organize, and make large amounts of data available. Its purpose is to enable uninterrupted organization of necessary information in your databases (DBs).

Compute Layer

It uses Massively Parallel Processing (MPP) clusters to allocate necessary compute resources for data loading, transformation, and querying. All the workloads are isolated within virtual warehouses (VWHs), and database access is specified to optimize performance and resource usage.

Cloud Services Layer

Cloud services enable communication with client apps for better user interaction. It includes aspects like infrastructure management, metadata management, access control, and security.

2. Performance & Resource Management

The Snowflake architecture paves the path for dynamic resource configuration, modification, and scaling. The SaaS platform adapts to different usage scenarios for the right resource allocation. Hence, you no longer have to manage resources manually or work with specialized DBs for distinct data formats.

3. Semi-Structured Data Handling

It offers native support for semi-structured data formats like JSON, XML, Avro, and Parquet. The VARIANT data type stores and manages semi-structured data within relational tables in its native form. Its schema-less storage ensures no information loss or any performance lag. Attributes are automatically discovered for finer data access and compression.

4. Elastic Scalability

Your growing and evolving business requires a platform with scalable performance and capacity as per workload demand. No need to plan or maintain capacity upfront.

Key Features and Capabilities of Snowflake Database

As companies generate an increasing amount of data, data warehousing solutions like Snowflake become increasingly important. Its distinct architecture is behind the extensive list of features that it brings to the table.

The United States, the UK, and India are among the top three geographies using Snowflake for data warehousing.

Here are a few that your organization can benefit from:

1. Multi-Cluster Shared Architecture

A visual representation of the multi-cluster shared data architecture of Snowflake

Snowflake’s architecture separates storage and compute, enabling them to scale independently and elastically. Businesses of different sizes can thus utilize them as intended. It also offers better flexibility at a higher cost-efficiency, a major limitation of traditional coupled systems.

2. Support for Structured & Semi-Structured Data

Snowflake supports structured and semi-structured data

Snowflake can work with both structured data (relational tables) and semi-structured data formats (JSON, Parquet, Avro, XML). It does not need any complex upfront transformations to make this happen. Its VARIANT data type enables highly flexible schema-on-read capabilities.

3. Supports Diverse Workloads

Key components of the Snowflake Data Cloud are deployed across all three major cloud providers

Even though it is a modern data warehouse, it supports workloads like data lakes, data science, data engineering, and data applications.

4. Flexible & Scalable

The Snowflake infrastructure can accommodate scaling data

The data platform offers you the space to instantly size compute resources either way, without any downtime or direct impact on your users. Increasing data volume automatically scales the storage. With this on-demand scalability, you only pay for the resources you use, saving unnecessary expenses.

5. Near-Zero Management

Snowflake is a fully managed SaaS platform that automates administrative tasks like software updates, infrastructure provisioning, performance tuning, and security patching. As the operational overhead remarkably reduces, you can focus on data analysis more than usual.

Benefits of Snowflake Data Warehouse

Snowflake’s architecture and features come together to produce tangible advantages. Upon using the SaaS platform, your organization can store raw data having actionable insights. And, how’s that possible, you may ask? Because of its sharp cloud-native design.

As of August 2024, the net retention rate of Snowflake was reported to be 127%. The high marker is evidence of the consistent customer loyalty and their growing investment in Snowflake services.

Here are a few key benefits of Snowflake data warehouse:

Benefits that make Snowflake data warehouse a great choice for you

1. Innovative Features

This platform features highly innovative capabilities, including Zero-Copy Cloning (for instant database copies) and Time Travel (for accessing historical data). These features tag along advantages like data recovery, development, testing, and auditing. They improve your data management efficiency and at reduced costs.

2. High Performance & Concurrency

The MPP architecture and automatic query optimization enable fast query execution. It supports multiple concurrent users and varying workloads without degrading performance.

Partners, business units, and customers can access governed and secure real-time data sharing without data duplication. It fosters a collaborative environment within your organization for new data monetization opportunities.

4. Cloud Integration & Multi-Cloud Support

Snowflake is built for the cloud and thus seamlessly integrates with all major cloud platforms, like AWS, GCP, and Azure. Your small business can benefit from cross-cloud data sharing for better flexibility and no vendor lock-in.

5. Extensive Ecosystem & Partner Integrations

Snowflake integrates seamlessly with various BI, data science, ETL/ELT (Extract, Transform, and Load/Extract, Load, and Transform), and other tools. Integration knits into a comprehensive ecosystem to fulfill all data-related needs. Snowflake Marketplace has further expanded easy access to distinct datasets and data services.

Snowflake Database Use Cases

Snowflake has risen to the top of the pyramid due to its exceptional features and consequent benefits. It has customers in almost all leading industries, and the number continues to rise. Here are a few Snowflake database use cases.

By industry categorization, IT services hold 21% of Snowflake’s customer base, followed by computer software at 13%, and financial services at 6%.

1. Information Technology and Services

Organizations in the IT sector often have gigantic operational data, performance metrics, and customer data. They thus require a highly flexible and scalable analytics platform. Snowflake optimizes operations and delivers high-quality services to your clients.

It helps in:

Optimizing service delivery for better service level agreements (SLAs)
Building data-driven services for different data needs
Improving efficiency for internal operations and analytics
Sharing and collaborating on data without duplication
Managing customer data and insights through a unified view

2. Computer Software

An organization in this industry must be generating and managing data around customer behavior, product usage, marketing efforts, and development processes. Snowflake data platform helps analyze this information for business growth, operational excellence, and product improvement.

It is useful in:

Customer behavior analysis for personalized sales and marketing efforts
Data sharing for internal collaboration
Efficiency boost in testing and development with zero-copy cloning
Product analysis for informed future development
SaaS platform analysis for valuable insights

3. Financial Services

The financial services sector has huge datasets, personalized customer interactions, and stringent regulatory requirements. There is a constant need for real-time risk assessment. Snowflake is a great platform for this sector as it presents a modern and scalable solution to tackle these issues.

Snowflake helps in:

Developing and executing algorithmic trading strategies
Sharing data for better collaboration
Integrating data for a comprehensive view of customers
Personalizing financial and banking advice
Analyzing transactional data for risk management and compliance

4. Manufacturing

Sensors, production lines, enterprise resource planning (ERP) systems, and supply chains generate data in huge quantities. Snowflake data platform integrates and analyzes this accumulated information for better quality, higher agility, and more efficiency.

Manufacturing companies benefit through:

End-to-end visibility for supply chain optimization
Real-time production data analysis for smart manufacturing
IoT data analytics for scalability
Reduced operational costs through predictive maintenance
Demand and plan production forecasts

5. Advertising, Entertainment & Media

Organizations in these industries have multiple content formats and platforms. They face a major challenge of unifying distinct data sources for a more comprehensive understanding of content performance and consumer behavior. You can break down these data silos with Snowflake’s elevated features.

It helps in:

Audience segmentation through its powerful query engine
Data monetization without compromising privacy
Data integration from advertising platforms for a unified customer view
Content performance analysis for better strategies
Personalized content delivery for improved user engagement

Snowflake Database – Your Reliable Cloud Solution

From startups to large enterprises, Snowflake database is a platform for everyone. Its speed, flexibility, and scalability make it your go-to cloud solution for handling gigantic data volumes and related challenges. It ensures a future-proof data infrastructure to simplify data operations.

Experts at Aegis utilize Snowflake’s capabilities to ensure an impactful and seamless transition to a high-performing and reliable cloud solution. From designing custom Snowflake data warehouses to managing secure data loading, optimizing query performance, and integrating advanced AI/ML models, we have expertise in all. Our hands-on implementation and strategic guidance ensure that the Snowflake environment is a revolution for your business.

Are you ready to transform your data space? Contact our Snowflake consulting services to discuss how we can revolutionize your data.

FAQs

Q1. What is Snowflake database used for?

Snowflake database is used for storing, processing, and analyzing data in huge volumes. It gives your organization a fully managed, secure, and scalable environment for data sharing, data warehousing, and data lakes.