Snowflake’s Time Travel lets you retrieve and analyze historical data for recovery and compliance. This guide outlines its practical applications with DbVisualizer.
Use cases
Historical data queries
Time Travel allows you to analyze data as it existed at specific moments. Whether for recovery or trend analysis, querying historical data is simple:
SELECT *
FROM your_table
AT(TIMESTAMP => '2023-08-13 01:00:00'::timestamp);
Table restoration
Restoring a table to its prior state can resolve errors or recover lost data. Time Travel simplifies this task.
INSERT INTO new_table
SELECT *
FROM original_table
AT(TIMESTAMP => '2023-08-06 01:00:00'::timestamp);
Auditing modifications
Tracking changes over time is essential for compliance. A stream setup in Snowflake captures all modifications to your data:
CREATE OR REPLACE STREAM change_stream ON TABLE your_table;
FAQ
What’s the purpose of Time Travel?
To access and query past data versions for analysis and recovery.
Can Time Travel aid compliance?
Yes, it enables detailed tracking of data modifications for audits.
What benefits does DbVisualizer bring?
It integrates with Snowflake to simplify querying and visualization.
How does Time Travel handle retention?
Retention is configurable and defines how far back data can be queried.
Summary
Snowflake Time Travel is a valuable tool for historical data analysis and auditing, especially when used with DbVisualizer. Explore more details in the article Leveraging Snowflake's Time Travel.
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