AWS Database Blog

Category: Learning Levels

Index types supported in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL (GIN, GiST, HASH, BRIN)

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.

Index types supported in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL (B-tree)

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.

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.

Optimize data validation using AWS DMS validation-only tasks

AWS DMS provides the capability to validate your data as you migrate from various supported sources to AWS. Data integrity and accuracy is one of key requirements we often hear about from our customers that determines a successful migration project. In this post, we delve deep into AWS DMS data validation feature. We explore its benefits, configurations, and use cases.

Build secure multi-party computation (MPC) wallets using AWS Nitro Enclaves

Different types of blockchain applications and users demand varying types of private key management solutions, referred to as wallets. Custodial wallets are managed by third-party vendors such as a centralized crypto exchange, whereas non-custodial wallets give you full control and ownership over your private keys and funds. In this post, we focus on multi-party computation (MPC) wallets. We introduce the core concepts of MPC wallets, including the security features they offer that make MPC wallets uniquely well suited for institutional customers. We also detail the most critical aspects of implementing a distributed, highly secure MPC wallet on AWS, including a design for a single MPC cosigner that uses AWS Nitro Enclaves to protect the most sensitive information: the key shards.

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.