Posted On: Oct 22, 2020
You can now export HAQM Relational Database Service (HAQM RDS) or HAQM Aurora snapshots to HAQM S3 as Apache Parquet format in additional regions. Parquet is an efficient open columnar storage format for analytics and is up to 2x faster to export and consumes up to 6x less storage in HAQM S3, compared to other text formats. You can analyze the exported data with other AWS services such as HAQM Athena, HAQM EMR, and HAQM SageMaker.
You can create an export with just a few clicks on the HAQM 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 instance. The extracted data in Apache Parquet format is portable, so you can consume it with query services such as HAQM Athena or big data processing frameworks such as Apache Spark. For more information, including instructions on getting started, read the Aurora documentation or HAQM RDS documentation.
HAQM RDS Snapshot Export to S3 can export data from HAQM RDS for PostgreSQL, HAQM RDS for MariaDB, HAQM RDS for MySQL, HAQM Aurora with PostgreSQL compatibility, and HAQM Aurora with MySQL compatibility snapshots. It is now available in US West (N. California), Canada (Central), Europe (London), Europe (Paris), Europe (Frankfurt), Europe (Stockholm), Europe (Milan), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Hong Kong), Asia Pacific (Sydney), Asia Pacific (Mumbai), South America (Sao Paulo), Middle East (Bahrain), and Africa (Cape Town). Snapshot Export to S3 was previously already available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Tokyo) regions.
HAQM 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 HAQM Aurora by visiting the product page.