AWS Database Blog

Category: Database

Scale your Amazon MemoryDB for Redis clusters at a lower cost with data tiering

Amazon MemoryDB for Redis is a Redis-compatible database service that delivers both in-memory performance and Multi-AZ durability. You can use MemoryDB as a primary database for use cases that require durable storage and ultra-fast performance, like user session data, message streaming between microservices, payment processing, gaming leaderboards, and Internet of Things (IoT). Today, we announced […]

Amazon DynamoDB schema from the prism of SQL

A database is one of the main components of software system design. RDBMS has been a cornerstone of application development for decades, making SQL the language of choice for most developers. As application requirements for scalability and availability are changing rapidly, Amazon DynamoDB—a serverless, NoSQL key-value database that delivers single-digit millisecond performance at any scale […]

Enable change data capture on Amazon RDS for MySQL applications that are using XA transactions

XA transactions are not a very familiar concept to lots of people and therefore hardly used. An XA transaction is a two-phase commit protocol that supports distributed transactions that updates multiple relational databases. It involves a transaction manager that monitors this global transaction. XA makes sure that transactional updates are committed in all of the […]

Migrate Oracle hierarchical queries to Amazon Aurora PostgreSQL

We have seen a number of organizations are migrating their database workloads from commercial database engines to the Amazon Aurora database environment. These organizations have reduced their overall efforts on common database administration tasks, data center maintenance, and have moved away from proprietary database features and commercial licenses. AWS provides the AWS Schema Conversion Tool […]

Validate database objects after migrating from SAP ASE to Amazon RDS for MySQL, Amazon RDS for MariaDB, or Amazon Aurora MySQL

In this post, we focus on database object validation for the heterogenous migration from SAP ASE to Amazon Relational Database Service (Amazon RDS) for MySQL, Amazon RDS for MariaDB, or Amazon Aurora MySQL-Compatible Edition. For schema conversion and migration, you can use AWS Schema Conversion Tool (AWS SCT). AWS SCT helps convert your database schema […]

Empowering fraud detection at Delivery Hero with Amazon Neptune

This is a guest post co-authored by Amr Elnaggar, Saurabh Deshpande, Mohammad Azzam, Matias Pons and Wilson Tang from Delivery Hero. Delivery Hero is available in 74 countries around the World. It operates a wide range of local brands that are united behind the shared mission Always Delivering an Amazing Experience — fast, easy, and […]

Enable notifications for block corruption on Amazon RDS for Oracle

Consistency is one of the most crucial characteristics of relational database systems. Even though every system has their own mechanisms for providing consistency based on the database engine, sometimes you may lack consistency for several reasons, such as I/O hardware and firmware, OS issues, the database engine software, and recovering from UNRECOVERABLE or NOLOGGING database […]

How OLX optimized their Amazon DynamoDB costs by scaling their query patterns

This is a guest post by Miguel Alpendre (Engineering Manager at OLX Group), Rodrigo Lopes (Senior Software Engineer at OLX Group), and Carlos Tarilonte (Senior Developer at OLX Group) in partnership with Luís Rodrigues Soares (Solution Architect at AWS). At OLX, we operate the world’s fastest-growing network of trading platforms. Serving 300 million people every […]

Demystifying Amazon RDS backup storage costs

Amazon Relational Database Service (Amazon RDS) is a managed service that makes it easy to set up, operate, and scale relational databases in the cloud. Amazon RDS gives you access to the capabilities of a familiar MySQL, MariaDB, Oracle, SQL Server, or PostgreSQL database. Amazon RDS provides two different methods for backing up and restoring […]

Up your game: Increase player retention with ML-powered matchmaking using Amazon Aurora ML and Amazon SageMaker

Organizations are looking for ways to better leverage their data to improve their business operations. With Amazon Aurora, Aurora Machine Learning, and Amazon SageMaker, you can train machine learning (ML) services quickly and directly integrate the ML model with your existing Aurora data to better serve your customers. In this post, we demonstrate how a […]