Category: Technical How-to

Amazon’s Finance Technologies Tax team (FinTech Tax) manages mission-critical services for tax computation, deduction, remittance, and reporting across global jurisdictions. The Application processes billions of transactions annually across multiple international marketplaces. In this post, we show how the team implemented tiered tax withholding using Amazon DynamoDB transactions and conditional writes.

Text-to-SQL can automatically transform analytical questions into executable SQL code for enhanced data accessibility and streamlined data exploration, from analyzing sales data and monitoring performance metrics to assessing customer feedback. In this post, we explore how to use Amazon Relational Database Service (Amazon RDS) for PostgreSQL and Amazon Bedrock to build a generative AI text-to-SQL chatbot application using Retrieval Augmented Generation (RAG). We’ll also see how we can use Amazon MemoryDB with vector search to provide semantic caching to further accelerate this solution.

Careem powers rides, deliveries, and payments across the Middle East, North Africa and South Asia. As Careem grew, so did its data infrastructure challenges. Their monolithic 270 TB Amazon RDS for MySQL database consisting of one writer and five read replicas— experienced performance issues due to increased storage utilization, slow queries, high replica lag, and increased Amazon RDS cost. In this post, we provide a step-by-step breakdown of how Careem successfully implemented a phased data purging strategy, improving DB performance while addressing key technical challenges.

In this post, we show how you can use Amazon CloudWatch Database Insights for troubleshooting your Amazon RDS and Amazon Aurora resources. CloudWatch Database Insights serves as a database observability solution offering a tailored experience for DevOps engineers, application developers, and database administrators. This tool is designed to accelerate database troubleshooting processes and address issues across entire database fleets, enhancing overall operational efficiency.

In this post, we explore a streamlined solution that uses AWS Lambda and Python to read and ingest CSV data into an existing Amazon DynamoDB table. This approach adheres to organizational security restrictions, supports infrastructure as code (IaC) for table management, and provides an event-driven process for ingesting CSV datasets into DynamoDB.

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server gives you enhanced control through OS shell-level access and database administrator privileges. With this control comes the shared responsibility model, which requires you to manage your own OS and database patching. Operating system (OS) changes made after instance creation aren’t persistent. To maintain OS-level customizations, […]

In Oracle, UDTs can have member functions written in PL/SQL that are integrated directly into the UDT. In contrast, PostgreSQL currently doesn’t allow member functions within UDTs. In this post, we dive deep into these differences and provide guidance for a smooth migration, helping ensure that the integrity of your data models is maintained throughout the process. We will also walk you through the details of converting complex member type functions in the multi-nested UDT from Oracle to PostgreSQL.

Authorization systems are a critical component of modern applications, yet traditional approaches like role-based access control (RBAC) and attribute-based access control (ABAC) struggle to meet the complex access control requirements of today’s enterprises. In this post, we introduce a relationship-based access control (ReBAC) as an alternative for enterprise scale authorization. We explore how the proposed […]

We are excited to announce the availability of new features in AWS Database Migration Service (AWS DMS) replication engine version 3.5.4. This release includes two major enhancements: data masking for enhanced security and improved data validation performance. In this post, we deep dive into these two features. Refer to the release notes to see a list of all the new features available in this version.

Habby is a game studio that creates interactive entertainment to connect players worldwide. We adopted Valkey GLIDE, a client library for Amazon ElastiCache for Valkey and Redis OSS, to address our system challenges. Our system uses the Amazon ElastiCache for Redis OSS publish/subscribe (Pub/Sub) functionality for the chat message sending. However, we faced challenges with connection stability during infrastructure changes, such as instance scaling, Redis OSS version upgrades, and hardware failures. This post describes our messaging system architecture and explains how we improved system reliability by using Valkey GLIDE as the client communicating with Amazon ElastiCache.