Category: Amazon Aurora

Schneider Electric is a leader in digital transformation in energy management and industrial automation. To effectively manage customer account hierarchies in its CRM at scale, Schneider Electric started leveraging advances in generative artificial intelligence (AI) large language models (LLMs) in April 2023. They created a solution to make timely updates to their customer account hierarchies in their CRM by linking customer account information to the correct parent company based on the latest information retrieved from the Internet and proprietary datasets. In this post, we explore further iterations of this project and how the team applied what they learned to the Salesforce CRM system using Amazon Aurora and Amazon Bedrock.

Ola Money is a financial service provided by Ola Financial Services (OFS), which is part of the Ola group of companies. In this post, we share the modernization journey of Ola Money’s MySQL workloads using Amazon Aurora, a relational database management system built for the cloud with MySQL and PostgreSQL compatibility that gives the performance and availability of commercial-grade databases at one-tenth the cost.

As customers are migrating to the AWS Cloud to take advantage of managed database services such as Amazon RDS for MySQL, Amazon RDS for MariaDB, and Amazon Aurora MySQL-Compatible Edition, they also look to automate these administrative tasks. This post shows how a DBA or other user with access to a custom API can make MySQL and MariaDB backup requests. It uses Infrastructure as Code (IaC) with the AWS CDK to simplify the deployment.

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 demonstrate a process for migrating an Amazon QLDB ledger into Amazon Aurora PostgreSQL using the US Department of Motor Vehicles (DMV) sample ledger from the tutorial in the Amazon QLDB Developer Guide as an example. You may use this solution as a foundation for your own migration, altering it as necessary for your schema and migration strategy.

In this post, we discuss how to use Amazon Aurora PostgreSQL-Compatible Edition as an alternative to Amazon QLDB for auditing and what features of Amazon Aurora PostgreSQL can replace some of the unique capabilities offered by Amazon QLDB.

In this post, we discuss other native indexes supported in Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL, including GIN, GiST, HASH, and BRIN, and their use cases.

In this series of posts, we discuss index types supported in Amazon Aurora PostgreSQL-Compatible edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL and their use cases. In this post, we discuss the native B-tree index and its variations.

MoneyLion is a financial technology ecosystem leader with a mission to empower everyone to make their best financial decisions. The MoneyLion app delivers curated financial content and innovative products, including features to save and invest, integrating offers from over 1,100 enterprise partners. In this post, we share how MoneyLion achieved cost-optimization using Amazon Aurora I/O- Optimized, a new storage configuration in Amazon Aurora that provides improved price-performance and predictable pricing for I/O-intensive applications.

In this post, we explore the key factors to consider when selecting a database for your generative AI applications. We focus on high-level considerations and service characteristics that are relevant to fully managed databases with vector search capabilities currently available on AWS. We examine how these databases differ in terms of their behavior and performance, and provide guidance on how to make an informed decision based on your specific requirements.