Menu
AWS Schema Conversion Tool
User Guide (Version 1.0)

Document History

The following table describes the important changes to the AWS Schema Conversion Tool user guide after January 2018.

You can subscribe to an RSS feed to be notified of updates to this documentation.

Change Description Date
AWS SCT build #1.0.616

Updates include support RDS when converting from Oracle to Amazon RDS for Oracle, converting Oracle schedule objects, and support for Oracle jobs. partitioning, and Db2 LUW version 10.1.

June 26, 2018
AWS SCT build #1.0.615

Updates include support for SQL Server to PostgreSQL GOTO statements, PostgreSQL 10 partitioning, and Db2 LUW version 10.1.

May 24, 2018
AWS SCT build #1.0.614

Updates include support for Oracle to Oracle DB Links, SQL Server to PostgreSQL inline functions, and emulation of Oracle system objects.

April 25, 2018
AWS SCT build #1.0.613

Updates include support for Db2 LUW, conversion of SQL*Plus files, and SQL Server Windows Authentication.

March 28, 2018
AWS SCT build #1.0.612

Updates include support for custom data type mapping, schema compare for Oracle 10, and Oracle to PostgreSQL conversion of global variables.

February 22, 2018
AWS SCT build #1.0.611

Updates include support for Oracle to PostgreSQL dynamic statements, opening the log file by selecting an error message, and the ability to hide schemas in tree view.

January 23, 2018

Earlier Updates

The following table describes the important changes to the AWS Schema Conversion Tool user guide prior to January 2018.

Version Change Description Date Changed

1.0.608

FIPS endpoint support for Amazon S3

You can now request AWS SCT to connect to Amazon S3 and Amazon Redshift by using FIPS endpoints to comply with Federal Information Processing Standard security requirements. For more information, see Storing AWS Credentials.

November 17, 2017

1.0.607

FIPS endpoint support for Amazon S3

You can now request AWS SCT to connect to Amazon S3 and Amazon Redshift by using FIPS endpoints to comply with Federal Information Processing Standard security requirements. For more information, see Storing AWS Credentials.

October 30, 2017

1.0.607

Data extraction tasks can ignore LOBs

When you create data extraction tasks, you can now choose to ignore large objects (LOBs) to reduce the amount of data that you extract. For more information, see Creating, Running, and Monitoring an AWS SCT Data Extraction Task.

October 30, 2017

1.0.605

Data extraction agent task log access

You can now access the data extraction agent task log from a convenient link in the AWS Schema Conversion Tool user interface. For more information, see Creating, Running, and Monitoring an AWS SCT Data Extraction Task.

August 28, 2017

1.0.604

Converter enhancements

The AWS Schema Conversion Tool engine has been enhanced to offer improved conversions for heterogeneous migrations.

June 24, 2017

1.0.603

Data extraction agents support filters

You can now filter the data that the extraction agents extract from your data warehouse. For more information, see Creating Data Extraction Filters in the AWS Schema Conversion Tool.

June 16, 2017

1.0.603

AWS SCT supports additional data warehouse versions

You can now use the AWS Schema Conversion Tool to convert your Terradata 13 and Oracle Data Warehouse 10 schemas to equivalent Amazon Redshift schemas. For more information, see Converting Data Warehouse Schemas to Amazon Redshift Using the AWS Schema Conversion Tool.

June 16, 2017

1.0.602

Data extraction agents support additional data warehouses

You can now use data extraction agents to extract data from your Microsoft SQL Server data warehouses. For more information, see Using Data Extraction Agents.

May 11, 2017

1.0.602

Data extraction agents can copy data to Amazon Redshift

Data extraction agents now have three upload modes. You can now specify whether to just extract your data, to extract your data and just upload it to Amazon S3, or to extract, upload, and copy your data directly into Amazon Redshift. For more information, see Creating, Running, and Monitoring an AWS SCT Data Extraction Task.

May 11, 2017

1.0.601

AWS SCT supports additional data warehouses

You can now use the AWS Schema Conversion Tool to convert your Vertica and Microsoft SQL Server schemas to equivalent Amazon Redshift schemas. For more information, see Converting Data Warehouse Schemas to Amazon Redshift Using the AWS Schema Conversion Tool.

April 18, 2017

1.0.601

Data extraction agents support additional data warehouses

You can now use data extraction agents to extract data from your Greenplum, Netezza, and Vertica data warehouses. For more information, see Using Data Extraction Agents.

April 18, 2017

1.0.601

Data extraction agents support additional operating systems

You can now install data extraction agents on computers running the macOS and Microsoft Windows operating systems. For more information, see Installing Extraction Agents.

April 18, 2017

1.0.601

Data extraction agents upload to Amazon S3 automatically

Data extraction agents now upload your extracted data to Amazon S3 automatically. For more information, see Data Extraction Task Output.

April 18, 2017

1.0.600

Data Extraction Agents

You can now install data extraction agents that extract data from your data warehouse and prepare it for use with Amazon Redshift. You can use the AWS Schema Conversion Tool to register the agents and create data extraction tasks for them. For more information, see Using Data Extraction Agents.

February 16, 2017

1.0.600

Customer Feedback

You can now provide feedback about the AWS Schema Conversion Tool. You can file a bug report, you can submit a feature request, or you can provide general information. For more information, see Providing Customer Feedback.

February 16, 2017

1.0.502

Integration with AWS DMS

You can now use the AWS Schema Conversion Tool to create AWS DMS endpoints and tasks. You can run and monitor the tasks from AWS SCT. For more information, see Using the AWS Schema Conversion Tool with the AWS Database Migration Service .

December 20, 2016

1.0.502

Amazon Aurora with PostgreSQL compatibility as a target database

The AWS Schema Conversion Tool now supports Amazon Aurora with PostgreSQL compatibility as a target database. For more information, see Converting Database Schemas Using the AWS Schema Conversion Tool.

December 20, 2016

1.0.502

Support for profiles

You can now store different profiles in the AWS Schema Conversion Tool and easily switch between them. For more information, see Using AWS Service Profiles in the AWS Schema Conversion Tool.

December 20, 2016

1.0.501

Support for Greenplum Database and Netezza

You can now use the AWS Schema Conversion Tool to convert your data warehouse schemas from Greenplum Database and Netezza to Amazon Redshift. For more information, see Converting Data Warehouse Schemas to Amazon Redshift Using the AWS Schema Conversion Tool.

November 17, 2016

1.0.501

Redshift optimization

You can now use the AWS Schema Conversion Tool to optimize your Amazon Redshift databases. For more information, see Optimizing Amazon Redshift by Using the AWS Schema Conversion Tool.

November 17, 2016

1.0.500

Mapping rules

Before you convert your schema with the AWS Schema Conversion Tool, you can now set up rules that change the data type of columns, move objects from one schema to another, and change the names of objects. For more information, see Creating Mapping Rules in the AWS Schema Conversion Tool.

October 4, 2016

1.0.500

Move to cloud

You can now use the AWS Schema Conversion Tool to copy your existing on-premises database schema to an Amazon RDS DB instance running the same engine. You can use this feature to analyze potential cost savings of moving to the cloud and of changing your license type. For more information, see AWS Schema Conversion Tool Assessment Report.

October 4, 2016

1.0.400

Data warehouse schema conversions

You can now use the AWS Schema Conversion Tool to convert your data warehouse schemas from Oracle and Teradata to Amazon Redshift. For more information, see Converting Data Warehouse Schemas to Amazon Redshift Using the AWS Schema Conversion Tool.

July 13, 2016

1.0.400

Application SQL conversions

You can now use the AWS Schema Conversion Tool to convert SQL in your C++, C#, Java, or other application code. For more information, see Converting Application SQL Using the AWS Schema Conversion Tool.

July 13, 2016

1.0.400

New feature

The AWS Schema Conversion Tool now contains an extension pack and a wizard to help you install, create, and configure AWS Lambda functions and Python libraries to provide email, job scheduling, and other features. For more information, see Using the AWS Lambda Functions from the AWS SCT Extension Pack and Using the Custom Python Library for the AWS SCT Extension Pack.

July 13, 2016

1.0.301

SSL Support

You can now use Secure Sockets Layer (SSL) to connect to your source database when you use the AWS Schema Conversion Tool.

May 19, 2016

1.0.203

New feature

Adds support for MySQL and PostgreSQL as source databases for conversions.

April 11, 2016

1.0.202

Maintenance release

Adds support for editing the converted SQL that was generated for the target database engine. Adds improved selection capabilities in the source database and target DB instance tree views. Adds support for connecting to an Oracle source database using Transparent Network Substrate (TNS) names.

March 2, 2016

1.0.200

Maintenance release

Adds support for PostgreSQL as a target database engine. Adds the ability to generate converted schema as scripts and to save the scripts to files prior to applying the schema to the target DB instance.

January 14, 2016

1.0.103

Maintenance release

Adds offline project capability, the ability to check for new versions, and memory and performance management.

December 2, 2015

1.0.101

Maintenance release

Adds the Create New Database Migration Project wizard. Adds the ability to save the database migration assessment report as a PDF file.

October 19, 2015

1.0.100

Preview release

Provides the user guide for the AWS Schema Conversion Tool preview release.

October 7, 2015

On this page: