This architectural diagram gives a quick summary of how these features work and how they can be used together with other AWS services. Federated Query to be able, from a Redshift cluster, to query across data stored in the cluster, in your S3 data lake, and in one or more Amazon Relational Database Service (RDS) for PostgreSQL and Amazon Aurora PostgreSQL databases.Data Lake Export to unload data from a Redshift cluster to S3 in Apache Parquet format, an efficient open columnar storage format optimized for analytics.

Today, we are launching two new features to help you improve the way you manage your data warehouse and integrate with a data lake: To get information from unstructured data that would not fit in a data warehouse, you can build a data lake. A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. With a data lake built on Amazon Simple Storage Service (Amazon S3), you can easily run big data analytics and use machine learning to gain insights from your semi-structured (such as JSON, XML) and unstructured datasets. Amazon Redshift is a fast, fully managed data warehouse that makes it simple and cost-effective to analyze data using standard SQL and existing Business Intelligence (BI) tools. A data warehouse is a database optimized to analyze relational data coming from transactional systems and line of business applications.

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