Snowflake Basics: Time Travel

Snowflake Basics: Time Travel

Learn how to query historical data in Snowflake using Time Travel feature.

Introduction to Time Travel in Snowflake

Time Travel in Snowflake allows users to access historical data at any point within a defined retention period.

This feature is beneficial for recovering lost data or analyzing data changes over time.

Time Travel is enabled by default for all tables.

Understanding Time Travel Retention Period

Snowflake provides a default retention period of 1 day for all tables, which can be extended up to 90 days for enterprise accounts.

Users can access data from the past by specifying a timestamp or a specific query ID.

Retention periods are configurable per table.

Querying Historical Data

To query historical data, use the clause with a timestamp or clause with a query ID.

For example, to retrieve data as of a specific timestamp, use: .

Ensure the timestamp is within the retention period.

Best Practices for Time Travel

Limit the use of Time Travel to necessary cases to avoid performance issues.

Regularly review and clean up the data to manage storage costs.

Consider using the function for convenience.

Quick Checklist

• Understand the retention period for your tables.
• Familiarize yourself with the syntax for querying historical data.
• Implement best practices to optimize performance.

FAQ

What is Time Travel in Snowflake?

Time Travel allows users to access historical data within a defined retention period.

How long can I access historical data?

The default retention period is 1 day, which can be extended up to 90 days for enterprise accounts.

What is the syntax for querying historical data?

Use the clause with a timestamp or clause with a query ID.

Related Reading

• Snowflake Documentation
• Data Recovery Techniques
• Understanding Snowflake Architecture

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This tutorial is for educational purposes. Validate in a non-production environment before applying to live systems.

Tags: Snowflake, Time Travel, Data Engineering, BI Development

Quick Checklist

• Prerequisites (tools/versions) are listed clearly.
• Setup steps are complete and reproducible.
• Include at least one runnable code example (SQL/Python/YAML).
• Explain why each step matters (not just how).
• Add Troubleshooting/FAQ for common errors.

Applied Example

Mini-project idea: Implement an incremental load in dbt using a staging table and a window function for change detection. Show model SQL, configs, and a quick test.

FAQ

What versions/tools are required?

List exact versions of Snowflake/dbt/Airflow/SQL client to avoid env drift.

How do I test locally?

Use a dev schema and seed sample data; add one unit test and one data test.

Common error: permission denied?

Check warehouse/role/database privileges; verify object ownership for DDL/DML.