Category: Amazon RDS

In this blog post, we will highlight how ZS Associates used multiple AWS services to build a highly scalable, highly performant, clinical document search platform. This platform is an advanced information retrieval system engineered to assist healthcare professionals and researchers in navigating vast repositories of medical documents, medical literature, research articles, clinical guidelines, protocol documents, […]

In this post, I’ll walk you through how to copy data from one Amazon Relational Database Service (Amazon RDS) for PostgreSQL database to another, while scrubbing PII along the way using AWS Glue. You will learn how to prepare a multi-account environment to access the databases from AWS Glue, and how to model an ETL data flow that automatically masks PII as part of the transfer process, so that no sensitive information will be copied to the target database in its original form.

Modern business applications rely on timely and accurate data with increasing demand for real-time analytics. There is a growing need for efficient and scalable data storage solutions. Data at times is stored in different datasets and needs to be consolidated before meaningful and complete insights can be drawn from the datasets. This is where replication […]

Amazon Relational Database Service (Amazon RDS) for MySQL zero-ETL integration with Amazon Redshift was announced in preview at AWS re:Invent 2023 for Amazon RDS for MySQL version 8.0.28 or higher. In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation […]

For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. This is where the Retrieval Augmented Generation (RAG) technique comes in. RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. For ingesting these […]

AWS Glue is a serverless data integrating service that you can use to catalog data and prepare for analytics. With AWS Glue, you can discover your data, develop scripts to transform sources into targets, and schedule and run extract, transform, and load (ETL) jobs in a serverless environment. AWS Glue jobs are responsible for running […]

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue, Amazon EMR, and Amazon Redshift. You can visually build the workflow by wiring individual data pipeline tasks and configuring payloads, retries, […]

The post Archive and Purge Data for Amazon RDS for PostgreSQL and Amazon Aurora with PostgreSQL Compatibility using pg_partman and Amazon S3 proposes data archival as a critical part of data management and shows how to efficiently use PostgreSQL’s native range partition to partition current (hot) data with pg_partman and archive historical (cold) data in […]

Nowadays many customers are following a multi-cloud strategy. They might choose to use various cloud-managed services, such as Amazon Relational Database Service (Amazon RDS) for SQL Server and Azure SQL Managed Instances, to perform data analytics tasks, but still use traditional extract, transform, and load (ETL) tools to integrate and process the data. However, traditional ETL tools may […]

This is post is co-authored by Manish Mehra, Anirudh Vohra, Sidrah Sayyad, and Abhishek I S (from ZS), and Parnab Basak (from AWS). The team at ZS collaborated closely with AWS to build a modern, cloud-native data orchestration platform. ZS is a management consulting and technology firm focused on transforming global healthcare and beyond. We […]