AWS Database Blog

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.

In this post, we discuss a design for a highly searchable movie content graph database built on Amazon Neptune, a managed graph database service. We demonstrate how to build a list of relevant movies matching a user’s search criteria through the powerful combination of lexical, semantic, and graphical similarity methods using Neptune, Amazon OpenSearch Service, and Neptune Machine Learning. To match, we compare movies with similar text as well as similar vector embeddings. We use both sentence and graph neural network (GNN) models to build these embeddings.

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.

AWS has partnered with InfluxData to launch Amazon Timestream for InfluxDB, a managed version of the popular InfluxDB 2.x open source time series database engine. In this post, we demonstrate how to use the AWS InfluxDB migration script to migrate your data from your existing InfluxDB OSS 2.x instances to Timestream for InfluxDB. At the end of this post, we show one way to perform a live migration, with additional AWS resources.

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 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.

Starting with the Amazon Neptune engine version 1.3.2.X, openCypher query performance is up to 9 times faster and provides up to 10 times higher throughput than previous engine releases. You can create a new cluster or upgrade to this release for faster query performance, more open source features, and additional benefits.

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.

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.