AWS Database Blog

Category: Database

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 […]

How NXP performs event-driven RDF imports to Amazon Neptune using AWS Lambda and SPARQL UPDATE LOAD

For manufacturers it’s important to track transformations and transfers of products as they travel through the supply chain. In the event of quality issues, the ability to quickly and accurately identify a defective product and gather data for root cause analysis and containment is critical. NXP Semiconductors has been working to improve its product traceability […]

Migrate your SQL Server workload with CLR integration to AWS

Common language runtime (CLR) integration is an option to host .NET code within SQL Server programmatic objects like stored procedures, functions, and triggers, and adding user-defined data types. Since its introduction in SQL Server 2005, CLR integration has gained popularity within the SQL Server community for its additional flexibility and options to import .NET code […]

Build resilient applications with Amazon DynamoDB global tables: Part 4

In the first three posts of this four-part series, you learned how the choice of zonal or Regional services impacts availability, and some important characteristics of Amazon DynamoDB when used in a multi-Region context with global tables. Part 1 also covered the motivation for using multiple Regions. Part 2 discussed some important characteristics of DynamoDB. […]

Build resilient applications with Amazon DynamoDB global tables: Part 3

In the first two posts of this four-part series, you learned how the choice of zonal or Regional services impacts availability and some important characteristics of Amazon DynamoDB when used in a multi-Region context with global tables. Part 1 also covered the motivation for using multiple AWS Regions. Part 2 discussed some important characteristics of […]

Build resilient applications with Amazon DynamoDB global tables: Part 2

In the first post of this series, you learned about the differences between zonal, Regional, and global services, and how they affect theoretical application availability. In this post, you’ll learn more about some important Amazon DynamoDB characteristics and how they impact multi-Region design. Properties of DynamoDB tables in a single Region DynamoDB is a NoSQL […]

Build resilient applications with Amazon DynamoDB global tables: Part 1

Customers that need to build resilient applications with the lowest possible recovery time objective (RTO) and recovery point objective (RPO) want to make the best use of AWS global infrastructure to support their resilience goals. Building an application using multiple Availability Zones in a single AWS Region can provide high levels of availability, but you […]

Adding real-time machine learning predictions to Amazon Aurora: Part 1

Businesses today want to enhance the data stored in their relational databases and incorporate up-to-the-minute predictions from machine learning (ML) models. However, most ML processing is done offline in separate systems, resulting in delays in receiving ML inferences for use in applications. AWS wants to make it efficient to incorporate real-time model inferences in your […]

Configure a performance testing framework for Amazon Aurora PostgreSQL

In this post, we demonstrate how you can use AWS CloudFormation, open-source Apache JMeter, and Python to generate a performance testing framework for Amazon Aurora PostgreSQL-Compatible Edition databases. This performance testing model can help you run multiple iterations of load testing on Aurora PostgreSQL and make data-driven decisions regarding the database version, configuration, and instance […]