Snowflake rapidly gains attention in the Cloud data platform industry. Compared to traditional data warehouses, Snowflake offers significant advantages in scalability, performance, and ease of management, and the technology is selected by leading companies.
This article provides an overview of the key reasons behind Snowflake’s growing popularity and its key technical features.
Snowflake is a cloud-native data platform that integrates Data Warehouse (DWH), Data Lake, and Data Engineering functionalities. Snowflake operates on Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), offering flexible scalability and high performance.
Source : https://docs.snowflake.com/ja/user-guide/intro-regions
Snowflake was founded in 2012; it went public on the New York Stock Exchange (NYSE) in 2020. They achieved the largest IPO by a cloud company at the time. Since then, it has rapidly gained global adoption, and many companies are now using it as their data analytics platform.
Snowflake is a DWH designed specifically for clouds, unlike traditional on-premises ones. This means there is no need for infrastructure management, and resources can be easily scaled up or down.
Snowflake is known for separating compute instance and data storage, which offers several key benefits as follows:
Source : https://docs.snowflake.com/ja/user-guide/intro-key-concepts
Snowflake encrypts data by default with robust features for access control and audit logs. As the other advantage, its data-sharing enables secure data to be shared between different organizations and teams.
Source : https://www.snowflake.com/ja/data-cloud/workloads/collaboration/?utm_cta=website-homepage-workload-card-ai-m
Snowflake includes build-in features such as automatic data compression, index optimization, and caching, enables fast query execution. Especially, its resume feature (pause and resume) allows compute resources to be used efficiently as needed.
Snowflake allows seamless integration of various data sources (CSV, JSON, Parquet) and smooth connectivity with external BI tools (Tableau, Power BI, Looker).
Additionally, its Data Marketplace enables businesses to purchase and utilize third-party data.
Snowflake has 3 different types of architectures such as storage, compute, and cloud services.
Migrate existing on-premises DWHs (Oracle, Teradata, IBM) to the cloud in order to achieve scalability and cost optimization.
Integrate a Data Lake with Snowflake for unified management of both structured and unstructured data.
Perform real-time data analysis by integrating with tools such as Tableau and Power BI.
Aggregate training data for machine learning models on Snowflake and integrate with AI tools such as Databricks, AWS SageMaker, and Google Vertex AI.
Snowflake’s pricing is divided into 2 main components, storage and compute costs:
It operates on a pay-as-you-go basis, where you are charged only for the services you use, ensuring maximum cost efficiency.
Snowflake has become an increasingly popular platform worldwide, recognized as the ideal solution for leveraging data in the cloud area. For companies considering modernizing their data warehouses or establishing a foundation for data analytics, it presents a highly valuable option.
| Main Features | Benefit |
|---|---|
| Cloud-native | Excellent scalability without infrastructure management |
| Separation of Compute and Storage | Cost optimization, performance improvement |
| Security and Data sharing capabilities | Safe management and sharing of data |
| Query Performance Optimization | Enables fast data processing |
| Support for various data formats | Easy integration of JSON, CSV, Parquet |
| Easy integration with external tool | Integration with Tableau, Power BI, AI tools |
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In the next article, we will drive into the responsibilities of Avaxia Snowflake team, its perspective on the distinctions between data scientists and data engineers. Stay tuned!
