AWS Database Blog

Category: Advanced (300)

Turn petabytes of relational database records into a cost-efficient audit trail using Amazon Athena, AWS DMS, Amazon RDS, and Amazon S3

In this post, we show how you can use AWS Database Migration Service (AWS DMS) to migrate relational data from Amazon RDS into compressed archives on Amazon S3. We discuss partitioning strategies for the resulting archive objects and how to use S3 Object Lock to protect the archive objects from modification. Lastly, we demonstrate how to query the archive objects using SQL syntax through Athena with seconds latency, even on large datasets.

Automate interval partitioning maintenance and monitoring in Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL – Part 2

In Part 1 of this series, we demonstrated how to configure interval partitioning in an Amazon Aurora PostgreSQL-Compatible Edition database using PostgreSQL extensions such as pg_partman and pg_cron. The monitoring job was external to the database, thereby allowing a centralized monitoring solution. In this post, we demonstrate how you can monitor and send alerts using […]

A hybrid approach for homogeneous migration to an Amazon DocumentDB elastic cluster

Today, customers use document databases for many different types of applications. For example, gaming clients use them for handling users’ attribute information, while a stock application employs a document-oriented database to store chronological quote data. As the number of documents grows over time, you need more compute and storage than what is traditionally offered through […]

Scale your connections with Amazon DocumentDB using mongobetween

Amazon DocumentDB (with MongoDB compatibility) is a fully managed native JSON document database that makes it easy and cost-effective to operate critical document workloads at virtually any scale without managing infrastructure. You can use the same application code written using MongoDB API (versions 3.6, 4.0, and 5.0) compatible drivers, and tools to run, manage, and […]

Right-sizing Amazon RDS for Db2 by replaying the Db2 LUW workload

Amazon Relational Database Service (Amazon RDS) for Db2 makes it easy to set up, operate, and scale Db2 deployments in the cloud. Db2 is an IBM relational database that supports large-scale transactional and analytical workloads. Amazon RDS for Db2 handles time-consuming database administrative tasks, such as hardware provisioning, software patching, and backup management, freeing you […]

How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora PostgreSQL

LeadSquared is a new-age software as a service (SaaS) customer relationship management (CRM) platform that provides end-to-end sales, marketing, and onboarding solutions. Tailored for sectors like BFSI (banking, financial services, and insurance), healthcare, education, real estate, and more, LeadSquared provides a personalized approach for businesses of every scale. LeadSquared Service CRM goes beyond basic ticketing, […]

Provision and manage Amazon RDS for Oracle using Terraform

This the first post in a multi-part series where we discuss how you can set up Amazon Relational Database Service (Amazon RDS) for Oracle with Terraform. Terraform by HashiCorp allows you to define the instructions for setting up the infrastructure as a code, simplifying and automating the process instead of doing everything manually. Overview of […]

How Agnostic Engineering improved storage latency for running Polygon nodes on AWS

This is a guest post co-written by Arnaud Briche, the Founder of Agnostic. At Agnostic, our mission is to democratize access to well-structured blockchain data. We aim to provide a swift, user-friendly, and robust method for querying the vast volumes of data generated by smart contract blockchains. As a company, for performance reasons we first […]

A generative AI use case using Amazon RDS for SQL Server as a vector data store

Generative artificial intelligence (AI) has reached a turning point, capturing everyone’s imaginations. Integrating generative capabilities into customer-facing services and solutions has become critical. Current generative AI offerings are the culmination of a gradual evolution from machine learning and deep learning models. The leap from deep learning to generative AI is enabled by foundation models. Amazon […]