AWS Database Blog

Category: Intermediate (200)

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.

Create a Knowledge Graph application with metaphactory and Amazon Neptune

In a previous post, we described how to connect Amazon Neptune to metaphactory, securely, and then how to explore and search the Neptune graph data using metaphactory. In this post, we show how you can use metaphactory to build an end user application using its dynamic model driven components, driven by SPARQL queries.

Configure SSL encryption on an SAP ASE source endpoint in AWS DMS

In this post, we walk you through how to configure Secure Sockets Layer (SSL) encryption between the source endpoints in AWS DMS and an on-premises SAP ASE source for secure data transfer. We also show you the steps for enabling SSL on an on-premises SAP ASE database. Configuring SSL encryption on source endpoints enables encrypting data in transit during the database migration process for enhanced security.