You can try out macro conversion in the latest version of AWS SCT, available now. For example, consider the following Teradata table and macro: You can think of macros as simple stored procedures. Essentially, macros are SQL statements that accept parameters and can be called from multiple entry points in your application code. We’ll use Teradata as an example data warehouse. In this post, we introduce five new features: automation for macro conversion, support for case-insensitive string collation, support for case-sensitive database identifiers, recursive common table expressions (WITH clauses), and automatic table optimization, which tunes your Amazon Redshift tables based on your query workload. We show examples of how to use the new features and provide links to relevant documentation so you can continue exploring these new capabilities. This is the first in a series of posts that introduce dozens of new features to Amazon Redshift and AWS SCT in the areas of scripting, data type support, performance, and SQL enhancements. Today, we’re happy to share some recent enhancements to Amazon Redshift and the AWS Schema Conversion Tool (AWS SCT) that make it easier to automate your migrations to Amazon Redshift. You had to remediate syntax differences, inject code to replace proprietary features, and manually tune the performance of queries and reports. Until now, migrating a data warehouse to AWS was complex and involved a significant amount of manual effort. In these cases, you may have terabytes (or petabytes) of data, a heavy reliance on proprietary features, and thousands of extract, transform, and load (ETL) processes and reports built over years (or decades) of use. Many customers have asked for help migrating from self-managed data warehouse engines to Amazon Redshift. You can also integrate AWS services like Amazon EMR, Amazon Athena, Amazon SageMaker, AWS Glue, AWS Lake Formation, and Amazon Kinesis to take advantage of all of the analytic capabilities in the AWS Cloud. With Amazon Redshift, you can query exabytes of data across your data warehouse, operational data stores, and data lake using standard SQL. No other data warehouse makes it as easy to gain new insights from your data. Accelerate your data warehouse migration to Amazon Redshift – Part 6 to learn how to manage uniqueness constraints like primary keysĪmazon Redshift is the leading cloud data warehouse.Accelerate your data warehouse migration to Amazon Redshift – Part 5 to learn how to migrate set tables to Amazon Redshift.Accelerate your data warehouse migration to Amazon Redshift – Part 4 to learn about new options for database scripting. Accelerate your data warehouse migration to Amazon Redshift – Part 3 to learn about automation for proprietary SQL statements.Accelerate your data warehouse migration to Amazon Redshift – Part 2 to learn about automation for proprietary data types.Accelerate your data warehouse migration to Amazon Redshift – Part 1 to learn more about macro conversion, case-insensitive string comparison, and other new features.In this post (the first in a multi-part series), we describe new capabilities to automate your schema conversion, preserve your investment in existing scripts, reports, and applications, accelerate query performance, and reduce your overall cost to migrate to Amazon Redshift.
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