AWS Database Blog

Many organizations run IBM Db2 databases across multiple physical servers or virtual machines. This approach leads to resource investments in infrastructure, management, and licensing. Additionally, advancements in hardware technology, increased CPU capacities, and database engine enhancements result in underutilized servers if not rightsized at the outset. To optimize resource utilization, organizations can explore the following […]

In this post, we dive into the various architecture patterns and options available for both compute and storage layers while configuring your self-managed Oracle databases on Amazon EC2 to comply with your HA and DR requirements.

In this post, we examine the realities behind common myths about DynamoDB on-demand capacity mode across three key areas: cost implications and efficiency, operational overhead and management, and performance considerations. We provide practical guidance to help you make informed decisions about throughput management.

In this post, we show you several long-term data backup strategies and how to effectively implement them in the AWS environment, with a focus on Amazon Relational Database Service (Amazon RDS) and Amazon Aurora.

When using Secrets Manager to manage your master user passwords, you cannot create new read replicas for your database instance. This applies to all DB engines except Amazon RDS for SQL Server, potentially impacting your organization’s ability to efficiently scale its read operations while maintaining secure credential practices. In this post, we present a solution that automates the process of rotating passwords for a primary instance with read replicas while maintaining secure credential management practices. This approach allows you to take advantage of the benefits of both read scaling and automated credential rotation.

Many organizations rely on Windows Authentication and Kerberos for secure access to their SQL Server databases. When using Amazon RDS for SQL Server with a self-managed Active Directory, organizations can enhance their authentication beyond the default NTLM protocol to support Kerberos authentication. In this post, we show you how to manually configure and maintain Kerberos authentication for Amazon RDS for SQL Server DB instances joined to a self-managed Active Directory. We walk through the process of configuring service principal names (SPNs), adding necessary user principal name (UPN) suffixes, and automating SPN updates to handle failovers and host replacements.

In this post, we discuss how to migrate MySQL very large databases (VLDBs) from a self-managed MySQL database to Amazon Aurora MySQL-Compatible Edition using the MyDumper and MyLoader tools.

In this post, we explore the end-of-life (EOL) timeline for Aurora PostgreSQL and Amazon RDS for PostgreSQL. We discuss features in PostgreSQL major versions, Amazon RDS Extended Support, and various upgrade strategies, including in-place upgrades, Amazon RDS blue/green deployments, and out-of-place upgrades.

In this post, we highlight the scaling and performance challenges Mindbody was facing due to an increase in their data growth. We also present the root cause analysis and recommendations for adopting to Aurora Optimized Reads, outlining the steps taken to address these issues. Finally, we discuss the benefits Mindbody realized from implementing these changes, including enhanced query performance, significant cost savings, and improved price predictability.

In this post, we discuss the fully managed approach using Amazon Bedrock Knowledge Bases to simplify the integration of the data source with your generative AI application using Aurora. Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case.