AWS Database Blog
Category: Intermediate (200)
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.
How Gen replayed a database workload from Oracle to Amazon Aurora
In this post, we show you how the Gen team replayed an Oracle database workload for a mission-critical application on Amazon Aurora PostgreSQL-Compatible Edition.
Introducing Valkey GLIDE, an open source client library for Valkey and Redis open source
We’re excited to announce Valkey General Language Independent Driver for the Enterprise (GLIDE), an open source permissively licensed (Apache 2.0 license) Valkey client library. In this post, we discuss the benefits of Valkey GLIDE.
How to choose the best disaster recovery option for your Amazon Neptune database
In this post, we explore the key considerations and best practices for implementing effective DR strategies for your Amazon Neptune database deployments.