Announcing Amazon Relational Database Service (RDS) Snapshot Export to S3
You can now export Amazon Relational Database Service (Amazon RDS) or Amazon Aurora snapshots to Amazon S3 as Apache Parquet, an efficient open columnar storage format for analytics. The Parquet format is up to 2x faster to export and consumes up to 6x less storage in Amazon S3, compared to text formats. You can analyze the exported data with other AWS services such as Amazon Athena, Amazon EMR, and Amazon SageMaker.
You can now export Amazon Relational Database Service (Amazon RDS) or Amazon Aurora snapshots to Amazon S3 as Apache Parquet, an efficient open columnar storage format for analytics. The Parquet format is up to 2x faster to export and consumes up to 6x less storage in Amazon S3, compared to text formats. You can analyze the exported data with other AWS services such as Amazon Athena, Amazon EMR, and Amazon SageMaker.
You can create an export with just a few clicks on the Amazon RDS Management Console or using the AWS SDK or CLI. Extracting data from a snapshot doesn’t impact the performance of your database, as the export operation is performed on your snapshot and not your database. The extracted data in Apache Parquet format is portable, so you can consume it with query services such as Amazon Athena or big data processing frameworks such as Apache Spark. For more information, including instructions on getting started, read the Aurora documentation or Amazon RDS documentation.
Amazon RDS Snapshot Export to S3 can export data from Amazon RDS for PostgreSQL, Amazon RDS for MariaDB, Amazon RDS for MySQL, Amazon Aurora PostgreSQL, and Amazon Aurora MySQL snapshots and is now available in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Tokyo) Regions.
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. You can learn more about Amazon Aurora by visiting the product page.