AWS Database Blog

Tag: SCT

Convert JSON SQL queries from an Oracle database to a PostgreSQL database

Customers use semi-structured or unstructured data storage for various business use cases, which is schema-less and flexible in nature. One such type of semi-structured data is JavaScript Object Notation (JSON). JSON stores data in the form of KEY, VALUE, LIST, and ARRAY formats. Oracle Database stores JSON object data in CLOB data type columns. PostgreSQL […]

Validating database objects after migration using AWS SCT and AWS DMS

Database migration can be a complicated task. It presents all the challenges of changing your software platform, understanding source data complexity, data loss checks, thoroughly testing existing functionality, comparing application performance, and validating your data. AWS provides several tools and services that provide a pre-migration checklist and migration assessments. You can use the AWS Schema […]

AWS Schema Conversion Tool blog series: Introducing new features in build 617

We are excited to introduce a new version of the AWS Schema Conversion Tool (AWS SCT). This version includes support for table-valued function conversions, additional information in server-level assessment reports, and more. For those of you who are new to AWS SCT, this tool helps convert your existing database schema from one database engine to […]

AWS Schema Conversion Tool introduces new features in build 616

We are excited to introduce a new version of AWS Schema Conversion Tool (AWS SCT) that includes support for PostgreSQL 10 partitioning, a new server-level Assessment Report, support for table-valued functions, and more. For those of you who are new to AWS SCT, this tool helps convert your existing database schema from one database engine […]

Introducing schema compare in AWS Schema Conversion Tool

The AWS Schema Conversion Tool (AWS SCT) makes your database migrations more predictable. It does this by automatically converting the source database schema and most of the database code objects to a format compatible with the target database. We’re excited to announce a new feature in AWS SCT to enable schema comparison and synchronization for […]

Simplify Data Warehouse Migration to Amazon Redshift Using New AWS Schema Conversion Tool Features

The AWS Schema Conversion Tool (AWS SCT) makes heterogeneous database migrations more predictable by automatically converting the source database schema and most of the database code objects to a format compatible with the target database. To help with migration of on-premises data warehouses to Amazon Redshift, the new version of AWS SCT adds the following important […]

Integrating Teradata with Amazon Redshift Using the AWS Schema Conversion Tool

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 […]

Migrate Your Procedural SQL Code with the AWS Schema Conversion Tool

Database administrators and developers rely on relational databases to store data for applications. As Forbes noted in 2016, the development of open source offerings for database management systems like PostgreSQL is causing a growing number of enterprises to migrate to lower-cost solutions for their data storage. The move to the cloud often provides an excellent […]

How to Migrate Your Oracle Data Warehouse to Amazon Redshift Using AWS SCT and AWS DMS

Shree Kenghe is a solutions architect at Amazon Web Services. This blog post gives you a quick overview of how you can use the AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS) to help you migrate your existing Oracle data warehouse to Amazon Redshift. Amazon Redshift is a fast, fully […]