AWS Database Blog

Category: Intermediate (200)

Schneider Electric automates Salesforce account hierarchy management with generative artificial intelligence (AI) using Amazon Aurora and Amazon Bedrock

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.

Implement UUIDv7 in Amazon RDS for PostgreSQL using Trusted Language Extensions

UUID Version 7 (UUIDv7) was introduced to improve the randomness of UUIDv4. UUIDv7 encodes a Unix timestamp with millisecond precision in the first 48 bits of the UUID, meaning that UUIDv7 is time-based and sequential. Trusted Language Extensions (pg_tle) for PostgreSQL is a new open source development kit to help you build high performance extensions that run safely on PostgreSQL. In this post, we demonstrate how to create and install a Trusted Language Extension (TLE) using PL/Rust as the trusted language to generate a UUIDv7. We also take a deeper look into the underlying implementation of the extension.

Run an Ethereum staking service on Amazon EKS

In September 2022, Ethereum transitioned to a Proof of Stake (PoS) consensus model. This change allows anyone with a minimum of 32 ether to stake their holdings and operate a validator node, thereby participating in network validation and earning staking rewards. In this post, we explore the technical challenges and requirements of operating an institutional-grade Ethereum staking service. Additionally, we outline a solution for deploying an Ethereum staking service on AWS.

Ola Money achieved operational excellence, disaster recovery site in Asia Pacific (Hyderabad) Region, and up to 60% cost savings using Amazon Aurora

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.

Enhance database performance with Amazon RDS dedicated log volumes

For those seeking to achieve consistent database transaction performance, Amazon RDS has introduced a new feature: dedicated log volume (DLV). This feature is an additional storage volume specifically for database transaction logs. In this post, we examine common DLV performance benefits, use cases, monitoring capabilities, and the cost of deployment.

Replace Amazon QLDB with Amazon Aurora PostgreSQL for audit use cases

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.

How MoneyLion achieved price predictability and 55% cost-savings using Amazon Aurora I/O-Optimized and optimized RI purchases

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.

Key considerations when choosing a database for your generative AI 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.

Synopsis of several compelling features in PostgreSQL 16

In this post, we explore the new features in PostgreSQL 16 and discuss how they improve performance and query speed. This includes new replication features, including logical decoding on standbys and parallel application of logical replication, SQL/JSON functionality, new monitoring tools, such as the pg_stat_io system view, and security features.

Migrate from SAP ASE to SAP ASE on Amazon EC2 using AWS DMS and SAP ASE native methods

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.