Efficient Data Recovery with Snowflake Time Travel

Efficient Data Recovery with Snowflake Time Travel

Snowflake's Time Travel allows you to explore and recover historical data without complex backups. Paired with DbVisualizer, it provides an efficient way to manage and analyze data versions.

Examples of time travel use

Set up historical retention

Historical retention ensures your data changes are stored for a specific duration. Configuring this at the database level is simple:

CREATE OR REPLACE DATABASE my_database DATA_RETENTION_TIME_IN_DAYS = 30;

Query historical data

Historical data queries allow you to access and analyze data as it appeared at a specific point in time:

SELECT *
FROM your_table
AT(TIMESTAMP => '2023-08-13 01:00:00'::timestamp);

Audit changes

To keep track of modifications, you can use a Snowflake stream. This feature helps maintain an audit trail of all changes:

CREATE OR REPLACE STREAM change_stream ON TABLE your_table;

FAQ

What does Time Travel do?

It lets you access past data states within a retention window.

Can Time Travel help recover lost data?

Yes, you can restore tables to previous timestamps seamlessly.

Why combine Snowflake with DbVisualizer?

DbVisualizer simplifies data management and visualization for Snowflake users.

What are key use cases for Time Travel?

It’s ideal for auditing, compliance, and exploring historical trends.

Summary

Simplify data recovery and auditing with Snowflake's Time Travel. Use it alongside DbVisualizer for intuitive data management and analysis. Learn more reading the article Leveraging Snowflake's Time Travel.