AWS Big Data Blog

Code versioning using AWS Glue Studio and GitHub

AWS Glue now offers integration with Git, an open-source version control system widely used across the developer community. Thanks to this integration, you can incorporate your existing DevOps practices on AWS Glue jobs. AWS Glue is a serverless data integration service that helps you create jobs based on Apache Spark or Python to perform extract, […]

Upgrade to Athena engine version 3 to increase query performance and access more analytics features

Customers tell us they want to have stronger performance and lower costs for their data analytics applications and workloads. Customers also want to use AWS as a platform that hosts managed versions of their favorite open-source projects, which will frequently adopt the latest features from the open-source communities. With Amazon Athena engine version 3, we […]

Split your monolithic Apache Kafka clusters using Amazon MSK Serverless

Today, many companies are building real-time applications to improve their customer experience and get immediate insights from their data before it loses its value. As the result, companies have been facing increasing demand to provide data streaming services such as Apache Kafka for developers. To meet this demand, companies typically start with a small- or […]

Improve federated queries with predicate pushdown in Amazon Athena

In modern data architectures, it’s common to store data in multiple data sources. However, organizations embracing this approach still need insights from their data and require technologies that help them break down data silos. Amazon Athena is an interactive query service that makes it easy to analyze structured, unstructured, and semi-structured data stored in Amazon […]

Land data from databases to a data lake at scale using AWS Glue blueprints

To build a data lake on AWS, a common data ingestion pattern is to use AWS Glue jobs to perform extract, transform, and load (ETL) data from relational databases to Amazon Simple Storage Service (Amazon S3). A project often involves extracting hundreds of tables from source databases to the data lake raw layer. And for […]

Ingest streaming data to Apache Hudi tables using AWS Glue and Apache Hudi DeltaStreamer

In today’s world with technology modernization, the need for near-real-time streaming use cases has increased exponentially. Many customers are continuously consuming data from different sources, including databases, applications, IoT devices, and sensors. Organizations may need to ingest that streaming data into data lakes built on Amazon Simple Storage Service (Amazon S3). You may also need […]

Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Stream data processing allows you to act on data in real time. Real-time data analytics can help you have on-time and optimized responses while improving overall customer […]

Manage your Amazon QuickSight datasets more efficiently with the new user interface

Amazon QuickSight has launched a new user interface for dataset management. Previously, the dataset management experience was a popup dialog modal with limited space, and all functionality was displayed in this one small modal. The new dataset management experience replaces the existing popup dialog with a full-page experience, providing a clearer breakdown of a dataset’s […]

Automate data archival for Amazon Redshift time series tables

Amazon Redshift is a fast, petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse. You can […]

Design a data mesh with event streaming for real-time recommendations on AWS

This blog post was co-authored with Federico Piccinini. The data landscape has been changing in recent years: there is a proliferation of entities producing and consuming large quantities of data within companies, and for most of them defining a proper data strategy has become of fundamental importance. A modern data strategy gives you a comprehensive […]