This article was also posted on AWS’s blog here.
By Christian Romming, Founder and CEO at Etleap
Neeraja Rentachintala, Principal Product Manager with Amazon Redshift
Jobin George, Sr. Partner Solutions Architect at AWS
Caius Brindescu, Member of Technical Staff at Etleap
Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing extract, transform, and load (ETL), business intelligence (BI), and reporting tools.
Tens of thousands of customers use Amazon Redshift to process exabytes of data per day and power analytics workloads such as BI, predictive analytics, and real-time streaming analytics.
In this post, we discuss how Etleap integrates with new data sharing and cross-database querying capabilities in Amazon Redshift to enable workload isolation for diverse analytics use cases in customer environments.
Etleap is an AWS Advanced Technology Partner with the AWS Data & Analytics Competency and Amazon Redshift Service Ready designation.
Introduction to Etleap and New Amazon Redshift Capabilities
Etleap is a fully-managed ETL solution built specifically for Amazon Web Services (AWS) that doesn’t require extensive engineering work to set up, maintain, and scale. It reduces ETL setup time from months to days, automates most maintenance work, and provides transparency and full control over data pipelines.
Etleap integrates with any data source and runs either as a hosted solution (SaaS) or inside your virtual private cloud (VPC).
The new cross-database query capability in Amazon Redshift allows customers to query across databases in an Amazon Redshift cluster using a simple three-part notation <database>.<schema>.<table>.
Customers will continue to connect to a specific Amazon Redshift database from their BI and analytics tools, and applications via JDBC/ODBC similar to how they do today. Now, however, they can seamlessly query data from all the databases they have permissions to access on the cluster without having to connect to one database at a time.
The new Amazon Redshift data sharing capability allows customers to securely and easily share data across different Amazon Redshift clusters. Data sharing improves the agility of organizations by giving them instant, granular, and high-performance access to live data across Amazon Redshift clusters without the need to manually copy or move it.
Once data is shared, customers can use cross-database query functionality to query the shared databases from the consuming clusters and join the shared data with local data on the consumer cluster.
Continue reading “How Etleap Integrates with Amazon Redshift Data Sharing to Provide Isolation of ETL and BI Workloads” →