Snowflake is a cloud data warehousing solution that offers several unique features that give it an edge over other data warehouse solutions. Here are six of the distinctive features of Snowflake:

1. Major Cloud Platform Support: Snowflake is a cloud-agnostic solution that is available on all three major cloud providers: AWS, Azure, and GCP.

• • All major functionalities and features are available across the cloud providers.
  • This enables support for multiple cloud regions and organizations can host the instances based on their business requirements.
  • Pricing depends not on the cloud provider but on the snowflake edition that you are planning for your data platform.
  • You only pay for what you store and running compute. When compute is not used, you are not charged anything for compute.

 2.  Scalability: Snowflake is natively built using cloud technologies. Hence, it takes advantage of very high scalability, elasticity, & redundancy features. You can store more data and scale up or down your computing resources as needed.

• • Snowflake has implemented auto-scaling and auto-suspend features.
  • Auto-scaling feature enables Snowflake to automatically start and stop resource clusters during unpredictable load processing.
  • Auto-suspend feature stops the virtual warehouse when resource clusters have been sitting idle for a defined.

3.Near Zero Administration: Snowflake is a true SaaS offering with No hardware (virtual or physical) to select, install, configure, or manage.

1. • Snowflake handles Ongoing maintenance, management, upgrades, and tuning.
   • Companies can set up and manage their database solution without any significant involvement from DBA teams.
   • Storage, compute, cloud service, and data transfer monitoring and alerts (via notification & hard stop) are provided by Snowflake so compute credits can be managed by businesses very easily.

4. Support for Semi-Structured Data: Snowflake allows the storage of structured and semi- structured data.

• • Snowflake supports reading and loading of CSV, JSON, Parquet, AVRO, ORC, and XML files.
  • Snowflake can store semi-structured data with the help of a schema on read data type called VARIANT.
  • As data gets loaded, Snowflake parses the data, extracts the attributes, and stores it in a columnar format.
  • Snowflake supports ANSI SQL plus Extended SQL. You can query data using simple SQL statements. Snowflake extended SQL is very feature-rich and adds many useful libraries to help you become more productive.

    VARIANT datatype to store Semi-Structured Data

5.Time Travel and Fail Safe: As part of a continuous data protection lifecycle, snowflake allows you to access historical data (table, schema, or database) at any point within the defined retention period.

• • Time Travel allows Querying, cloning, and restoring historical data in tables, schemas, and databases based on the retention period. This retention period is adjustable between 0 to 90 days based on the Snowflake edition.
  • This feature can help in restoring data objects that might have been accidentally deleted or for duplicating or backing up data from key points in the past.
  • Fail Safe is a data recovery service that can be utilized after all other options have been exhausted.
  • It provides a 7-day time window during which Snowflake can retrieve prior data. This time begins after the Time Travel retention period expires.
  • Both these features require additional data storage and hence incur additional storage costs as well.

6.Continuous Data Loading: Snowflake has a Serverless component called Snow pipe, which can be integrated with external object storage like S3 or Azure Blob.

• • It facilitates rapid and automated data ingestion into Snowflake tables. It allows for immediate loading of data from files as soon as they become available.
  • It doesn’t require manual specification of a warehouse because Snowflake automatically provides the necessary resources for its execution.
  • Once set up, a Snow pipe automatically reads files that arrive in the source location and loads them into target tables without any manual execution or predefined schedule.
  • Snow pipe closely works with the other 2 objects called stream and task and these objects capture the data changes and their combination can help build micro-batch or CDC solutions.

Loading Files from Amazon S3 to Snowflake using Snow pipe

These are the few major distinguishing features of Snowflake Cloud Data Warehouse. Snowflake offers many other features that have made it a go-to Cloud Data Warehouse solution for countless enterprises.

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