To estimate what it will cost to run this walkthrough on AWS, you can use the AWS Pricing Calculator. Be sure to follow the instructions to delete resources at the end of this walkthrough to avoid additional charges. This walkthrough takes approximately two hours to complete. It then uses a SQL command script to install a sample schema and data onto the RDS Oracle DB instance that you then migrate to Amazon Redshift. (Optional) An SNS topic subscribed to the same event of object creation. A Lambda that triggers every time an object is created in the S3 bucket mentioned above. You can migrate your data and applications to Amazon Redshift in less time and with fewer changes than migrating to other analytics. An S3 bucket used by DMS as a target endpoint. Amazon Redshift is a cloud-native data warehouse platform built to handle workloads at scale, and it shares key similarities with Netezza that make it an excellent candidate to replace your on-premises appliance. This walkthrough uses a custom AWS CloudFormation template to create RDS DB instances for Oracle and Amazon Redshift. A DMS (Database Migration Service) instance replicating on-going changes to Redshift and S3. Perform postmigration activities such as creating additional indexes, enabling foreign keys, and making the necessary changes in the application to point to the new database. Although AWS DMS is capable of creating objects in the target as part of the load, it follows a minimalistic approach to efficiently migrate the data so that it doesn’t copy the entire schema structure from source to target. Identify and implement solutions to the issues reported by AWS SCT.ĭisable foreign keys or any other constraints that might impact the AWS DMS data load.ĪWS DMS loads the data from source to target using the Full Load approach. AWS SCT performs the necessary code conversion for objects like procedures and views. Generate the schema scripts and apply them on the target before performing the data load by using AWS DMS. We used Lambda in the middle to sample WAL files and move them to S3. Run the conversion report for Oracle to Amazon Redshift to identify the issues, limitations, and actions required for the schema conversion. The solution presented itself in reading WAL logs supplied by Postgres and using them to replicate data via S3 into Redshift.
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