Category: AWS Database Migration Service

Databases form a key part of any enterprise and managing databases during an M&A requires careful planning and implementation to ensure a smooth transition and to maintain data integrity. In this post, we highlight some of the key considerations for successful database management during a merger or acquisition spanning from data assessment to integration strategies.

In this post, we explore the steps to configure Oracle RAC as a source for AWS DMS.

AWS DMS provides the capability to validate your data as you migrate from various supported sources to AWS. Data integrity and accuracy is one of key requirements we often hear about from our customers that determines a successful migration project. In this post, we delve deep into AWS DMS data validation feature. We explore its benefits, configurations, and use cases.

In this post, we provide different options for data migration from an SAP ASE on-premises database to SAP ASE on Amazon Elastic Compute Cloud (Amazon EC2) based on the size of data, application downtime, and data compliance. The migration methods include using AWS Database Migration Service (AWS DMS) and SAP ASE native features.

In this post, we show you how the Gen team replayed an Oracle database workload for a mission-critical application on Amazon Aurora PostgreSQL-Compatible Edition.

With AWS DMS homogenous migration, you can migrate data from your source database to an equivalent engine on AWS using native database tools. In this post, we show you an example of a complete homogeneous migration process and provide troubleshooting steps for migrating from PostgreSQL to Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL.

In this post, we show how you can use AWS Database Migration Service (AWS DMS) to migrate relational data from Amazon RDS into compressed archives on Amazon S3. We discuss partitioning strategies for the resulting archive objects and how to use S3 Object Lock to protect the archive objects from modification. Lastly, we demonstrate how to query the archive objects using SQL syntax through Athena with seconds latency, even on large datasets.

Today, customers use document databases for many different types of applications. For example, gaming clients use them for handling users’ attribute information, while a stock application employs a document-oriented database to store chronological quote data. As the number of documents grows over time, you need more compute and storage than what is traditionally offered through […]

With AWS Database Migration Service (AWS DMS), you can migrate your data from relational databases and data warehouses to AWS or a combination of a cloud and on-premises configurations. In June 2023, AWS DMS Serverless was released, which automatically provisions, scales, and manages migration resources to make database migrations straightforward and more cost-effective. It removes the necessity of handling infrastructure tasks like capacity estimation, provisioning, cost-optimization, and managing versions and patching. In this post, we provide an overview of this new feature and present benchmarking results for two use cases.

AWS has introduced a new feature in AWS Database Migration Service (AWS DMS) that simplifies the migration of data from IBM Db2 databases with the Database Partitioning Feature (DPF) databases to Amazon Simple Storage Service (Amazon S3), a highly scalable and durable object storage service. With this new capability, you can now migrate your data from IBM Db2 DPF databases to Amazon S3, paving the way for building robust data lakes in the cloud. This new feature streamlines the migration process, provides data integrity, and minimizes the risk of data loss or corruption, even when dealing with large volumes of data distributed across multiple partitions and databases of varying sizes. In this post, we delve into the intricacies of this new AWS DMS feature and demonstrate how to implement it. We explore best practices for orchestrating data flows and optimizing the migration process, achieving a smooth transition from on-premises IBM Db2 DPF databases to a cloud-based data lake on Amazon S3.