AWS Database Blog

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.

In this series of posts, we walk through the process of creating a DynamoDB data model using an example multi-tenant application, a customer issue tracking service. The goal of this series is to explore areas that are important for decision-making and provide insights into the influences to help you plan your data model for a multi-tenant application. In this last part of the series, we explore how to validate the chosen data model from both a performance and a security perspective. Additionally, we cover how to extend the data model as new access patterns and requirements arise.

In this series of posts, we walk through the process of creating a DynamoDB data model using an example multi-tenant application, a customer issue tracking service. The goal of this series is to explore areas that are important for decision-making and provide insights into the influences to help you plan your data model for a multi-tenant application. In this post, we continue the design process, selecting a partition key design and creating our data schema. We also show how to implement the access patterns using the AWS Command Line Interface (AWS CLI).

In this series of posts, we walk through the process of creating a DynamoDB data model using an example multi-tenant application, a customer issue tracking service. The goal of this series is to explore areas that are important for decision-making and provide insights into the influences to help you plan your data model for a multi-tenant application. In this post, we define the access patterns and decide on the table design.

pgTAP (PostgreSQL Test Anything Protocol) is a unit testing framework that empowers developers to write and run tests directly within the database. In this post, we explore how to leverage the pgTAP extension for unit testing on Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL-Compatible Edition database, helping you build robust and reliable database applications.

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, […]