AWS Database Blog
Category: Intermediate (200)
Build low-latency, resilient applications with HAQM MemoryDB Multi-Region
On December 1, 2024, we announced the general availability of HAQM MemoryDB Multi-Region, a fully managed, active-active, multi-Region database that you can use to build applications with up to 99.999% availability, microsecond read, and single-digit millisecond write latencies across multiple Regions. In this post, we cover the benefits of MemoryDB Multi-Region, how it works, its disaster recovery capabilities, the consistency and conflict resolution mechanisms, and how to monitor replication lag across Regions.
Scheduled scaling of HAQM Aurora Serverless with HAQM EventBridge Scheduler
In this post, we demonstrate how you can implement scheduled scaling for Aurora Serverless using HAQM EventBridge Scheduler. By proactively adjusting minimum Aurora Capacity Units (ACUs), you can achieve faster scaling rates during peak periods while maintaining cost efficiency during low-demand times.
HAQM DocumentDB Quick Start: Zero Setup with AWS CloudShell
HAQM DocumentDB (with MongoDB compatibility) launched its integration with AWS CloudShell. With this integration, you can now connect to HAQM DocumentDB with a single click on the AWS Management Console without needing to perform any setup. In this post, we show how to connect to and work with HAQM DocumentDB using CloudShell. HAQM DocumentDB is […]
Demystifying HAQM DynamoDB on-demand capacity mode
In this post, we examine the realities behind common myths about DynamoDB on-demand capacity mode across three key areas: cost implications and efficiency, operational overhead and management, and performance considerations. We provide practical guidance to help you make informed decisions about throughput management.
Migrate very large databases to HAQM Aurora MySQL using MyDumper and MyLoader
In this post, we discuss how to migrate MySQL very large databases (VLDBs) from a self-managed MySQL database to HAQM Aurora MySQL-Compatible Edition using the MyDumper and MyLoader tools.
Upgrade strategies for HAQM Aurora PostgreSQL and HAQM RDS for PostgreSQL 12
In this post, we explore the end-of-life (EOL) timeline for Aurora PostgreSQL and HAQM RDS for PostgreSQL. We discuss features in PostgreSQL major versions, HAQM RDS Extended Support, and various upgrade strategies, including in-place upgrades, HAQM RDS blue/green deployments, and out-of-place upgrades.
How GaadiBazaar reduced database costs by 40% with Aurora MySQL Serverless
GaadiBazaar draws on over 25 years of vehicle finance expertise from Cholamandalam to connect vehicle buyers and sellers. Their mission is to enable hassle-free transactions at fair prices through buyer-seller interactions and end-to-end financial assistance. This post shows you how GaadiBazaar, an online platform for buying and selling vehicles, achieved significant database cost savings by migrating to HAQM Aurora MySQL Compatible Edition Serverless.
2024: A year of innovation and growth for HAQM DynamoDB
2024 marked a significant year for HAQM DynamoDB, with advancements in security, performance, cost-effectiveness, and integration capabilities. This year-in-review post highlights key developments that have enhanced the DynamoDB experience for our customers. Whether you’re a long-time DynamoDB user or just getting started, this post will guide you through the most impactful changes of 2024 and how they can help you build reliable, faster, and more secure applications. We’ve sorted the post by alphabetical feature areas, listing releases in reverse chronological order.
How Aqua Security exports query data from HAQM Aurora to deliver value to their customers at scale
Aqua Security is the pioneer in securing containerized cloud native applications from development to production. Like many organizations, Aqua faced the challenge of efficiently exporting and analyzing large volumes of data to meet their business requirements. Specifically, Aqua needed to export and query data at scale to share with their customers for continuous monitoring and security analysis. In this post, we explore how Aqua addressed this challenge by using aws_s3.query_export_to_s3 function with their HAQM Aurora PostgreSQL-Compatible Edition and AWS Step Functions to streamline their query output export process, enabling scalable and cost-effective data analysis.
Monitor the health of HAQM Aurora PostgreSQL instances in large-scale deployments
In this post, we show you how to achieve better visibility into the health of your HAQM Aurora PostgreSQL instances, proactively address potential issues, and maintain the smooth operation of your database infrastructure. The solution is designed to scale with your deployment, providing robust and reliable monitoring for even the largest fleets of instances.