AWS Big Data Blog
Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg
This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake (Apache Iceberg) using AWS Glue. We show how to build data pipelines using AWS Glue jobs, optimize them for both cost and performance, and implement schema evolution to automate manual tasks. To review the first part of the series, where we load SQL Server data into Amazon Simple Storage Service (Amazon S3) using AWS Database Migration Service (AWS DMS), see Modernize your legacy databases with AWS data lakes, Part 1: Migrate SQL Server using AWS DMS.
How SumUp built a low-latency feature store using Amazon EMR and Amazon Keyspaces
This post was co-authored by Vadym Dolin, Data Architect at SumUp. In their own words, SumUp is a leading financial technology company, operating across 35 markets on three continents. SumUp helps small businesses be successful by enabling them to accept card payments in-store, in-app, and online, in a simple, secure, and cost-effective way. Today, SumUp […]

