Are you looking for details about Time Travel in Snowflake? Are you also interested in knowing what are tasks we can perform using Time travel feature? If so, then you reached the right place. In this article, we will learn one of the powerful features is Snowflake.
A) What is Time Travel in Snowflake?
The feature by which we can access historical data at any point within a specified period is called Time Travel in snowflake we can access data not only changed but deleted as well.
B) What are the tasks that can be performed using Time travel in Snowflake?
The tasks below can be effectively performed by using Time Travel Feature
1. Backing up the data from key points in the past.
2. Duplicating the data from key points in the past.
3. Restoring tables, schemes, and databases if those are accidentally deleted.
C) What is Data Protection Lifecycle?
In snowflake, there are three-phase of the data protection lifecycles.
1. Current Data Storage: on the current data set we can perform standard operations such as DML , DDL etc.
2. Time Travel Retention: The normal retention period is 1 to 90 days. Here is the list of operations allowed with time travel.
a) SELECT .... AT| BEFORE ...
b) CLONE ... AT|BEFORE ...
C) UNDROP...
3. Fail safe: This is the last phase in Data Protection Lifecycle. This can only be performed by snowflake No user operations are allowed.
D) Data Retention Period in snowflake
In snowflake, Data Retention Period is a key component for Time Travel. The Data retention period specifies the period or number of days we can preserve data. Snowflake Preserves the state of data before update /delete/drop.
For Snowflake Standard Edition, the Data Retention period is one day.
For Snowflake Enterprise Edition, Data Retention Period between 0 to 90 days.
Learn more about Snowflake here -
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