Analyze RDS snapshot data using Amazon Athena

Question

My requirement is to find out how an Amazon RDS snapshot can be validated or proven to be not corrupted without actually restoring the snapshot. I came across information in the user guide at this link:
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ExportSnapshot.html

It mentions analyzing the snapshot data with Athena, but does not go into much detail.  I would like to know more about this possible solution to validating my RDS snapshots. How much effort/time would something like this take and what would the cost be? Also, are there other userguide pages I could reference for more about this or any other technique to validate my snapshots

re:Post Agent · Answer

Analyzing RDS snapshot data using Amazon Athena is indeed a viable approach to validate your snapshots without fully restoring them. Here's an overview of the process and considerations:

1. Export the RDS snapshot to Amazon S3: This is the first step, where you export your DB snapshot data to an S3 bucket. The data is stored in Apache Parquet format, which is compressed and consistent.

2. Set up Athena: Create a database in Athena to query the exported snapshot data. You'll need to create an external table that maps to the schema of your exported data.

3. Query the data: Use SQL queries in Athena to analyze the exported snapshot data. This allows you to verify the integrity and contents of your snapshot without a full restore.

The effort and time required depend on the size of your database and the complexity of your validation queries. For a basic setup and initial queries, it might take a few hours to a day. Costs include:

1. S3 storage costs for the exported snapshot
2. Athena query costs (you pay per TB of data scanned)
3. Data transfer costs if applicable

These costs are generally lower than performing a full restore of large databases.

To validate snapshots:

1. Check row counts and table structures
2. Verify key data points or run aggregate queries
3. Sample data from critical tables

While this method can help identify major issues, it may not catch all types of corruption. It's best used as part of a comprehensive backup validation strategy.

For more advanced analysis, you could use AWS Glue to transform the data and create a more detailed schema for querying. You might also consider using Amazon QuickSight for visualizing the results of your Athena queries, which can help in identifying patterns or anomalies in your snapshot data.

Remember that while this method is useful for validation, it doesn't replace proper backup and recovery testing, which should still be performed periodically.  
**Sources**  
[Exporting DB snapshot data to Amazon S3 for Amazon RDS - Amazon Relational Database Service](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ExportSnapshot.html)  
[Gather organization-wide Amazon RDS orphan snapshot insights using AWS Step Functions and Amazon QuickSight | AWS Database Blog](https://aws.amazon.com/blogs/database/gather-organization-wide-amazon-rds-orphan-snapshot-insights-using-aws-step-functions-and-amazon-quicksight/)  
[Programmatic approach to optimize the cost of Amazon RDS snapshots | AWS Database Blog](https://aws.amazon.com/blogs/database/programmatic-approach-to-optimize-the-cost-of-amazon-rds-snapshots/)

Analyze RDS snapshot data using Amazon Athena

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