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#Data types redshift how to
#Data types redshift drivers
#Data types redshift full
#Data types redshift code

We chose to launch with the AWS CloudFormation console to an existing VPC. If you have issues, visit the Teradata Community.įigure 3: AWS Marketplace and Teradata options These pre-steps are important to ensure a clean, easy setup. You can complete this process in a few minutes, which is impressive for all those who have waited days or weeks to get a Teradata onsite up and running.Ī few things that you should consider in advance are your key pair, virtual private cloud (VPC), and the security group to use with your Teradata instance.

#Data types redshift how to

For details on how to do this, see the Teradata on AWS Getting Started Guide. We selected a Teradata Database Developer instance on an i2.xlarge instance type.

#Data types redshift full

Lastly, AWS SCT supports point-in-time data extracts so that “change deltas” since the full load can be captured and migrated in a second step.įor this post, we use a Teradata instance from the AWS Marketplace to emulate a customer Teradata system.

In case of failure, an extraction process can restart from the point of failure, rather than from the beginning of the entire data extract.

Quickly move large numbers of records using multi-threaded data extraction and load processes.

The extractors were designed with the following two key capabilities to support the full load process: The AWS SCT extractors were designed to facilitate the full load process. Unlike OLTP databases, in which you can do a one-off full load followed by change data capture (CDC), for data warehouses, you can typically extract data and then load subsequent changes in batches using your application. You can use a similar approach to other data warehouses such as Oracle, IBM Netezza, Greenplum, HPE Vertica, and others.įigure 2: Supported conversion in AWS Schema Conversion Tool In this post, we focus on conversion from Teradata to Amazon Redshift. AWS SCT supports the conversions shown in the following diagram. The target database can be in Amazon RDS, Amazon EC2, or Amazon Redshift.

Your source database/data warehouse can be on-premises or in Amazon RDS or Amazon EC2. For information about supported source and target databases, see the AWS SCT User Guide.

#Data types redshift code

Any code that the tool can’t convert automatically is clearly marked so that you can convert it yourself. The custom code that the tool converts includes views, stored procedures, and functions. The AWS Schema Conversion Tool makes heterogeneous database migrations easy by automatically converting the source database schema and most of the custom code to a format that is compatible with the target database. Data load speed scales linearly with cluster size, with integrations to Amazon S3, Amazon DynamoDB, Amazon EMR, Amazon Kinesis, or any SSH-enabled host. You can also use standard PostgreSQL JDBC and ODBC drivers.

#Data types redshift drivers

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. Amazon Redshift delivers fast query performance by using columnar storage technology to improve I/O efficiency and parallelizing queries across multiple nodes. It provides a simple and cost-effective way to analyze all your data using your existing business intelligence (BI) tools. 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.Īmazon Redshift is a fast, fully managed, petabyte-scale, columnar, ANSI SQL-compliant data warehouse.

Most of these solutions run within the customer’s data center. Teradata has been a leading solution provider in the data warehousing space for decades, with many customers and workloads running on its solutions. In this post, we provide an example of how to integrate these two technologies easily and securely.Īt a high level, the architecture looks like the following diagram:įigure 1: Teradata to Amazon Redshift migration using AWS SCT agents 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. With this capability, you can easily integrate Teradata schemas into an Amazon Redshift model. Recently AWS announced support for Teradata as a source for the AWS Schema Conversion Tool (AWS SCT). As companies migrate to the cloud, they are using Amazon Redshift as part of their cloud adoption. Teradata provides long-standing data warehouse solutions, with many customers and applications running on its platforms. David Gardner is a solutions architect and Pratim Das is a specialist solutions architect for Analytics at Amazon Web Services.