Category: Amazon Aurora

Claroty is a leading provider of industrial cybersecurity solutions, protecting cyber-physical systems (CPS), such as industrial control systems, operational technology networks, and healthcare networks from cyber threats. Claroty’s business is rooted in its need to efficiently manage large volumes of data and run complex queries to ensure a great user experience for its customers who are reducing security risks to cyber-physical systems. One key workload involves an API that provides users with an interface to extract device, alert, and vulnerability data from the Claroty xDome dashboard, enabling seamless integration into their own data stores. In this post, we share how Claroty improved database performance and scaled Claroty xDome using the advanced features of Aurora.

This post outlines a set of design and tuning strategies for a high-speed purge in an Amazon Relational Database Service (Amazon RDS) for MySQL DB instance and Amazon Aurora MySQL-Compatible Edition DB cluster. Purge is a housekeeping operation in a MySQL database. The InnoDB storage engine relies on it to clean up undo logs and delete-marked table records that are no longer needed for multiversion concurrency control (MVCC) or rollback operations.

In this post, we show how you can visualize vector embeddings and explore semantic similarities. We use PCA for dimensionality reduction. PCA is a well-known dimensionality reduction technique that transforms high-dimensional data into a lower-dimensional space while preserving as much of the original variance as possible. By projecting data onto orthogonal axes called principal components, PCA enables you to visualize the underlying structure of the data in a more manageable form

In this post, we cover important concepts of Aurora provisioned and Aurora Serverless v2 databases including cost, performance, features, and how to determine which to use for your workload type.

In this post, we discuss the challenges with traditional data analytics mechanisms, our approach to solve them, and how you can use Amazon Aurora PostgreSQL-Compatible Edition zero-ETL integration with Amazon Redshift, which is generally available as of October 15th, 2024.

This post is a follow-up to How Zendesk tripled performance by moving a legacy system onto Amazon Aurora and Amazon Redshift. In this post, we go over the techniques we used to plan and upgrade major versions of Aurora PostgreSQL databases for Zendesk Explore with minimal customer downtime. We also discuss the performance optimizations we performed, the cost savings we achieved, and how we accomplished all of this within a period of 6 months. AWS Technical Account Managers played a significant role in helping us achieve these goals in a short period of time. The upgrade was performed successfully and without customer downtime.

April, 2026: Aurora Serverless v2 has been renamed Aurora serverless. No action required. AWS announced that Amazon Aurora Serverless v2 supports database capacity of up to 256 Aurora Capacity Units (ACUs). Aurora Serverless v2 is an on-demand, auto scaling configuration for Amazon Aurora. It adjusts capacity in fine-grained increments to provide the right amount of […]

In this post, we show how a large financial AWS customer achieved sub-minute failover between Availability Zones and single-digit minutes between AWS Regions. The customer partnered with AWS to engineer a solution to provide high availability (HA) and disaster recovery (DR) for their wealth management customer portal. The goals of the design were to minimize […]

In this post, we provide instructions to replicate ongoing changes using the change tracking feature available in SQL Server Web Edition (source) with the linked server feature available in the Babelfish for Aurora PostgreSQL (target).

In this post, we share the steps to connect to an Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL-Compatible Edition instance using a federated user with IAM Identity Center and IAM database authentication.To enhance security and streamline access, you can connect to your RDS or Aurora instances using federated users with AWS IAM Identity Center and AWS Identity and Access Management (IAM) database authentication. This integration allows you to manage database access through IAM Identity Center, providing secure, centralized authentication.