To make sure both Aurora MySQL DB instances can accept connections from the Amazon Redshift cluster, you should make sure that both your Amazon Redshift cluster and Aurora MySQL instances are in the same Amazon Virtual Private Cloud (Amazon VPC) and subnet group. To try this new feature, create a new Amazon Redshift cluster in a sql_preview maintenance track and Aurora MySQL instance and load sample TPC data into both data stores. In this post, we share information about how to get started with this new federated query feature to MySQL. Your data can then be more available to other analytics and machine learning (ML) tools, rather than siloed in disparate data stores. With this lake house architecture expansion to support more operational data stores, you can query and combine data more easily in real time and store data in open file formats in your Amazon Simple Storage Service (Amazon S3) data lake. Today, we’re launching a new feature of Amazon Redshift federated query to Amazon Aurora MySQL and Amazon RDS for MySQL to help you expand your operational databases in the MySQL family. We’re always listening to your feedback and, in April 2020, we announced general availability for federated querying to Amazon Aurora PostgreSQL and Amazon Relational Database Service (Amazon RDS) for PostgreSQL to enable you to query data across your operational databases, your data warehouse, and your data lake to gain faster and deeper insights not possible otherwise. Since we launched Amazon Redshift as a cloud data warehouse service more than seven years ago, tens of thousands of customers have built analytics workloads using it.
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