David Gardner is a solutions architect and Pratim Das is a specialist solutions architect for Analytics at Amazon Web Services.
Teradata provides long-standing data warehouse solutions, with many customers and applications running on its platforms. As companies migrate to the cloud, they are using Amazon Redshift as part of their cloud adoption. Recently AWS announced support for Teradata as a source for the AWS Schema Conversion Tool (AWS SCT). With this capability, you can easily integrate Teradata schemas into an Amazon Redshift model. Once both source and target schemas are in place, you can use AWS SCT to set up agents that collect and migrate data to the target Amazon Redshift schema. In this post, we provide an example of how to integrate these two technologies easily and securely.
Teradata has been a leading solution provider in the data warehousing space for decades, with many customers and workloads running on its solutions. Most of these solutions run within the customer’s data center. As companies begin to move to the cloud for its elasticity and speed to market, there is a need to integrate the rich datasets in these Teradata systems with systems in the cloud.
About Amazon Redshift
Amazon Redshift is a fast, fully managed, petabyte-scale, columnar, ANSI SQL-compliant data warehouse. It provides a simple and cost-effective way to analyze all your data using your existing business intelligence (BI) tools. Amazon Redshift delivers fast query performance by using columnar storage technology to improve I/O efficiency and parallelizing queries across multiple nodes. Amazon Redshift has custom JDBC and ODBC drivers that you can download from the Connect Client tab of the Amazon Redshift console, allowing you to use a wide range of familiar SQL clients. You can also use standard PostgreSQL JDBC and ODBC drivers. Data load speed scales linearly with cluster size, with integrations to Amazon S3, Amazon DynamoDB, Amazon EMR, Amazon Kinesis, or any SSH-enabled host.
Read more about this here.