Category: AWS Glue

June 2023: This post was reviewed and updated for accuracy. AWS Glue supports native integration with Apache Hudi, Delta Lake, and Apache Iceberg. Refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 2: AWS Glue Studio Visual Editor to learn more. Transactional data lake […]

August 2023: This post was reviewed and updated for accuracy. AWS Glue supports native integration with Apache Hudi, Delta Lake, and Apache Iceberg. Refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 2: AWS Glue Studio Visual Editor to learn more. Cloud data lakes […]

Social gaming and online sports betting are competitive environments. The game must be able to handle large volumes of unpredictable traffic while simultaneously promising zero downtime. In this domain, user retention is no longer just desirable, it’s critical. William Hill is a global online gambling company based in London, England, and it is the founding […]

Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price-performance. Tens of thousands of customers use Amazon Redshift to analyze exabytes of data per day and power analytics workloads such as BI, predictive analytics, and real-time streaming analytics without having to manage the data warehouse infrastructure. It natively integrates with other AWS […]

Jan 2024: This post was reviewed and updated for accuracy. Modern data architectures encourage the integration of data lakes, data warehouses, and purpose-built data stores, enabling unified governance and easy data movement. With a modern data architecture on AWS, you can store data in a data lake and use a ring of purpose-built data services […]

September 2023: This post was reviewed and updated for accuracy. Nowadays, many customers have built their data lakes as the core of their data analytic systems. In a typical use case of data lakes, many concurrent queries run to retrieve consistent snapshots of business insights by aggregating query results. A large volume of data constantly […]

March 2024: This post was reviewed and updated for accuracy. Most businesses store their critical data in a data lake, where you can bring data from various sources to a centralized storage. The data is processed by specialized big data compute engines, such as Amazon Athena for interactive queries, Amazon EMR for Apache Spark applications, […]

May 2023: This post was reviewed and updated with code to read and write data to Iceberg table using Native iceberg connector, in the Appendix section. As the implementation of data lakes and modern data architecture increases, customers’ expectations around its features also increase, which include ACID transaction, UPSERT, time travel, schema evolution, auto compaction, […]

This is post is co-authored by Jyothin Madari, Madhusudhan Muppagowni and Ayush Srivastava from GE. GE Proficy Manufacturing Data Cloud (MDC), part of the GE Digital’s Manufacturing Execution Systems (MES) suite of solutions, allows GED’s customers to increase the derived value easily and quickly from the MES by reliably bringing enterprise-wide manufacturing data into the […]

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. In 2019, Athena added support for federated queries to run SQL […]