Category: Advanced (300)

This is a three-part series in which we discuss the end-to-end process of building a data lake from a legacy SQL Server database. In this post, we show you how to build data pipelines to replicate data from Microsoft SQL Server to a data lake in Amazon S3 using AWS DMS. You can extend the solution presented in this post to other database engines like PostgreSQL, MySQL, and Oracle.

This is the third post in a series where we dive deep into performance testing of MySQL environments being migrated from on premises. In Part 1, we compared the query playback and traffic mirroring approaches at a high level. In Part 2, we showed how to set up and configure query playback. In this post, we show you how to set up and configure traffic mirroring.

This is the second post in a series where we dive deep into performance testing MySQL environments being migrated from on premises. In Part 1, we compared the query playback and traffic mirroring approaches at a high level. In this post, we dive into the setup and configuration of query playback.

Claroty is a leading provider of industrial cybersecurity solutions, protecting cyber-physical systems (CPS), such as industrial control systems, operational technology networks, and healthcare networks from cyber threats. Claroty’s business is rooted in its need to efficiently manage large volumes of data and run complex queries to ensure a great user experience for its customers who are reducing security risks to cyber-physical systems. One key workload involves an API that provides users with an interface to extract device, alert, and vulnerability data from the Claroty xDome dashboard, enabling seamless integration into their own data stores. In this post, we share how Claroty improved database performance and scaled Claroty xDome using the advanced features of Aurora.

In the post Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0, we discussed various ways to reduce costs by migrating your workload to Amazon DocumentDB. In this post, we demonstrate the document compression feature in Amazon DocumentDB to reduce storage usage and I/O cost.

In this post, we highlight common challenges encountered during homogeneous database migrations and how using AWS DMS homogeneous migration can help address them.

In this post, we show how you can visualize vector embeddings and explore semantic similarities. We use PCA for dimensionality reduction. PCA is a well-known dimensionality reduction technique that transforms high-dimensional data into a lower-dimensional space while preserving as much of the original variance as possible. By projecting data onto orthogonal axes called principal components, PCA enables you to visualize the underlying structure of the data in a more manageable form

In this post, we cover important concepts of Aurora provisioned and Aurora Serverless v2 databases including cost, performance, features, and how to determine which to use for your workload type.

In this post, we explore the fundamentals of building containerized applications for Amazon DocumentDB using Quarkus with the Panache ORM library. We cover the processes of containerizing your code, building an image, and deploying it using Amazon ECS with AWS Fargate.

Scopely is a global games developer, operator, and publisher with operations across North America, Central America, EMEA, and Asia, and additional studio partners spanning four continents. Over the past year, Scopely has served more than 500 million players with major titles such as “MONOPOLY GO!,” “Stumble Guys,” “MARVEL Strike Force,” “Star Trek Fleet Command,” and “Scrabble GO.” In this post, we showcase how Scopely used CloudBasix to enable migration of “Stumble Guys” high-volume backend transactional databases with minimal downtime from Azure SQL database to Amazon RDS for Server.