Category: AWS Database Migration Service

AWS Database Migration Service is a cloud service designed to simplify the process of migrating and replicating databases, data warehouses and other data stores. It offers a comprehensive solution for both homogeneous and heterogeneous database migrations, facilitating transitions between different database platforms. The migration process typically involves two major phases: Migration of existing data (full […]

Skello is a human resources (HR) software-as-a-service (SaaS) platform that focuses on employee scheduling and workforce management. It caters to various sectors, including hospitality, retail, healthcare, construction, and industry. In this post, we show how Skello uses AWS Database Migration Service (AWS DMS) to synchronize data from an monolithic architecture to microservices and perform data ingestion from the monolithic architecture and microservices to our data lake.

In this post, we discuss configurations in AWS DMS endpoints and AWS DMS tasks to migrate spatial columns from Oracle to Aurora PostgreSQL-Compatible efficiently.

In this post, we provide details on two PostgreSQL plugins available for use by AWS DMS. We compare these plugin options and share test results to help database administrators understand the best practices and benefits of each plugin when working on migrations.

The zero-ETL integrations for Amazon Redshift are designed to automate data movement into Amazon Redshift, eliminating the need for traditional ETL pipelines. With zero-ETL integrations, you can reduce operational overhead, lower costs, and accelerate your data-driven initiatives. This enables organizations to focus more on deriving actionable insights and less on managing the complexities of data integration. In this post, we discuss the best practices for migrating your ETL pipeline from AWS DMS to zero-ETL integrations for Amazon Redshift.

In How the Amazon TimeHub team designed resiliency and high availability for their data replication framework: Part 2, we covered different scenarios handling replication failures at the source database (Oracle), AWS DMS, and target database (Amazon Aurora PostgreSQL-Compatible Edition). As part of our resilience scenario testing, when there was a failover between the Oracle primary database instance and primary standby instances, and the database opened up with RESETLOGS, AWS DMS couldn’t automatically read the new set of logs in case of a new incarnation. In this post, we dive deep into the solution the Amazon TimeHub team used for detecting such a scenario and recovering from it. We then describe the post-recovery steps to validate and correct data discrepancies caused due to the failover scenario.

In How the Amazon Timehub team built a data replication framework using AWS DMS: Part 1, we covered how we built a low-latency replication solution to replicate data from an Oracle database using AWS DMS to Amazon Aurora PostgreSQL-Compatible Edition. In this post, we elaborate on our approach to address resilience of the ongoing replication between source and target databases.

This post is co-authored with Eric Boyer and Maria Hristova of Firmex. Firmex is a leading Virtual Data Room provider with more than 20,000 new rooms opened every year. In this post, we discuss how and why Firmex migrated 65,000 databases heterogeneously from their on-premises SQL Server to Amazon Aurora PostgreSQL-Compatible Edition.

Today, we’re excited to inform you about a new generative AI feature in DMS SC. You can now use advanced language models to streamline and enhance your migration workflow. In this post, we discuss the key capabilities of DMS SC with generative AI and how to enable it to offer you additional recommendations to reduce manual conversion effort and time.

We are excited to announce Amazon Timestream for LiveAnalytics as a newly supported target endpoint for AWS Database Migration Service (AWS DMS). This addition allows you to move time-series data from an AWS DMS supported source database to Timestream. In this post, we show you how to use Timestream as a target for an example PostgreSQL source endpoint in AWS DMS.