Skip to Content

Amazon Redshift Connector 1.0 – Mule 4

Posted on October 25, 2022 by

Categories: AWS

Tags:

You may connect to the Amazon Redshift database to carry out inserts, deletes, updates, and SQL queries using the Anypoint Connector for Amazon Redshift (also known as the Amazon Redshift Connector).

See the Amazon Redshift Connector Release Notes for details on compatibility and resolved problems.

Go to Before You Start

You need to be familiar with the following to utilize this connector:

  • The Redshift API from Amazon
  • Aware Connectors
  • Runtime for Mule (Mule)
  • A Mule flow’s components and global elements
  • Mule app development using Anypoint Studio (Studio)
  • To create an app, you need to have the following:
  • Login information for the Amazon Redshift target resource
  • Regardless Platform
  • at least Anypoint Studio 7.3
  • Jump to Typical Connector Use Cases

Typical Uses of the Connector

These are a few applications for this connector:

  • Analytics
  • A business intelligence (BI) solution like Tableau or Amazon Redshift’s customized data warehouse can store enormous amounts of data for later analysis.
  • Analyzing social media feeds in real-time.
  • To execute real-time analytics, stream data from your social media feeds, such as Twitter feed, into Amazon Kinesis Data Streams and then store it in a data warehouse, like Amazon Redshift.
  • Navigate to Authentication Types

As part of a trend toward serverless analytics options, AWS announced the public preview of Amazon Redshift Serverless. The latest version of the managed data warehouse service targets deployments where it is difficult to manage capacity due to variable workloads or unpredictable spikes.

Amazon Redshift Serverless supports JDBC/ODBC-compliant tools and the Redshift Data API and is designed for sporadic workloads, development and test environments, and ad-hoc business analytics, like anomaly detection or ML-based forecasting. Danilo Poccia, chief evangelist of EMEA at AWS, explains:

Amazon Redshift Serverless automatically provisions the right compute resources for you to get started. As your demand evolves with more concurrent users and new workloads, your data warehouse scales seamlessly and automatically to adapt to the changes. You can optionally specify the base data warehouse size to have additional control on cost and application-specific SLAs.

As for the serverless documentation, most of the features supported by an Amazon Redshift provisioned cluster are also supported on a serverless endpoint. Still, there are known issues and limitations during the preview, including the lack of public endpoints and support limited to a subset of availability zones and regions.

Types of Authentication

The connection techniques used by Amazon Redshift Connector are as follows:

Using user and password field values to access the database, basic authentication

To connect to the database using IAM authentication, the access key and secret fundamental field values are used to get the temporary password for the given user.