Snowflake is an analytic data warehouse on cloud provided as Software-as-a-Service (SaaS). The Snowflake database support ANSI SQL with added functionalities. It is faster and easier to use cloud data warehouse compared other cloud databases such as Redshift, Azure Synapse or GCP BigQuery. In this article, we will explain why you should learn Snowflake cloud database. We will also check the features that makes Snowflake a unique cloud database for data warehouse design.
Why You Should Learn Snowflake?
Snowflake is a cloud database specifically designed for a cloud. As per the official documents, Snowflake’s architecture is a hybrid of traditional shared-disk database architectures and shared-nothing database architectures. Snowflake has as a multi-cluster, a shared data architecture that is dynamic and highly scalable. Similar to shared-disk architectures, Snowflake uses a central data repository for persisted data that is accessible from all compute nodes in the data warehouse. Snowflake processes queries using MPP (massively parallel processing) compute clusters where each node in the cluster stores and process a portion of the entire data set locally.
Unique Architecture of Snowflake Database
The power of Snowflake lies in its unique architecture. Snowflake architecture contains three layers
- Database Storage
- Query Processing, and
- Cloud Services
The Snowflake database storage layer is where the Snowflake database stores all data in the form of highly efficient hybrid columnar storage to speed up the data retrieval. Snowflake compresses and stores the data in the micro-partition within a table.
Second layer, query processing layer consists of multiple virtual warehouses responsible for processing query tasks. Each virtual warehouse is an independent compute cluster that does not share compute resources with other virtual warehouses.
The third layer, cloud services layer coordinates the activities that take place when you access cloud data warehouse.
Cloud services includes
- Authentication
- Infrastructure management
- Metadata management
- Query parsing and optimization
- Access control
Free Trial Period
Snowflake allows 30 days free trial. When you create an account Snowflake will provide you with $400 worth of free usage. You can utilize the free credits to setup Snowflake cluster to make yourself familiar with the Snowflake.
User-friendly Interface
The snowflake interface is user-friendly for both users with and without coding experience. You perform your simple tasks such as ad-hoc query execution using Snowflake UI.
On-Demand Pricing
Snowflake offers on-demand pricing, that means you will only pay based on the amount of data you store and the compute hours/minutes you use.
Performance and Speed
With the help of multiple virtual warehouses, automatic query optimization, micro-partitions, the Snowflake architecture is designed to allow faster query processing. You can also create clustered tables to improve query performance if the table size is in terms of multi-terabytes.
Snowflake is Available on Major Three Cloud Platforms
You don’t have to switch the cloud service provider to use Snowflake. Initially, Snowflake was available only on Amazon AWS. Later, they provided support for other two cloud platforms, namely, GCP and Microsoft Azure.
Data Lake Support
Snowflake is also the only cloud database that can be used as a data warehouse and a data lake. You can query the data files stored on S3 bucket by creating a stage object. This means that you no longer need to have a separate data lake and data warehouse.
Zero Administration Cost
The best part about Snowflake it is fully automated and zero administration cost. You don’t have to worry about configuration, software updates, failures, or scaling your infrastructure as your data size and number of users grow. Snowflake supports modern features such as auto-scaling warehouse size, auto suspends, workload management, and data sharing.
Tools Support
Snowflake allows you to connect almost all modern ETL tools such as Informatica, DataStage, etc. It also allows you to connect all major BI tools such as Tableau, Power BI, etc.
JavaScript Support
The traditional databases such as Oracle, Teradata supports PLSQL statements to procedures and functions. Snowflake supports JavaScript that allows you to write procedures and functions.
Programming Languages Support
You can query Snowflake tables from almost all major programming languages such as Python, R, Java, .NET, Go, C, Node.js, etc.
Support Different File Formats
Snowflake supports both structured data, such as CSV, TSV, etc. and semi-structured data, including JSON, XML, Parquet, Avro, ORC.
Encryption and Security
By default, Snowflake encrypts all customer data at rest and in transit at no additional cost. You have full control over who has access to your data. They make it easy to maintain strong security with access management controls.
Easy Data Sharing
The Snowflake architecture allows seamless data sharing between consumers and providers. You can share your data with any recipients even if they’re not Snowflake clients. You can create read-only accounts and share your data with anyone.
Related Articles,
- How to Handle Error in Snowflake Procedures and Functions?
- Replace Function in Snowflake – Usage and Examples
- How to Handle NULL in Snowflake? Functions
- Best Methods to Compare Two Tables in SQL
- How to Use Translate Function in Snowflake?
- How to Get Rows Affected by Last Snowflake SQL Query?
- Working with External Tables in Amazon Redshift?
- Working with Snowflake Scripting Stored Procedures
Hope this helps 🙂