Fail-safe is a non-configurable feature in Snowflake that provides an additional layer of data protection beyond Time Travel. Time Travel allows users to access historical data within a configurable period (up to 90 days), while Fail-safe provides an additional 7-day period during which Snowflake retains historical data to recover from significant data loss or corruption incidents. This period is not accessible by users but can be used by Snowflake support to assist in data recovery efforts.
Reference: Snowflake Documentation on Fail-safe and Time Travel

Snowflake's Data Exchange allows data providers to publish data that is accessible only to users they explicitly invite. This mechanism ensures that only approved users or Snowflake accounts have access, adding a layer of security and control. Invited users can query the shared data directly within their Snowflake account without requiring data copies, reducing redundancy and enhancing data accessibility within controlled boundaries. This selective sharing feature is part of Snowflake's secure data-sharing capabilities.

Snowflake supports semi-structured data types that can store complex data structures within a single column. The VARIANT data type can hold structured and semi-structured data formats such as JSON, Avro, ORC, Parquet, and XML. The ARRAY data type is also used for semi-structured data and can store an ordered list of elements. These data types enable users to work with semi-structured data directly in Snowflake without needing to flatten the data into a relational schema first.
Reference: Snowflake Documentation on Semi-Structured Data Types

Snowflake's architecture allows for flexibility in account hosting across different cloud vendors and regions. This means that within a single organization, different Snowflake accounts can be set up in various cloud environments, such as AWS, Azure, or GCP, and in different geographical regions. This allows organizations to leverage the global infrastructure of multiple cloud providers and optimize their data storage and computing needs based on regional requirements, data sovereignty laws, and other considerations.
https://docs.snowflake.com/en/user-guide/intro-regions.html

Snowflake credits are the unit of measure for the compute resources used in Snowflake. The number of credits consumed depends on the size of the virtual warehouse and the time it is running. Larger warehouses consume more credits per hour than smaller ones, and credits are billed for the time the warehouse is active, regardless of the actual usage within that time.
References: [COF-C02] SnowPro Core Certification Exam Study Guide