AWS Big Data Blog

Category: Announcements

AWS and DuckLabs: Building the future of analytics together

Today we are announcing that Amazon has signed a definitive agreement to acquire DuckLabs, the Amsterdam-based company behind the open-source analytical database DuckDB. We expect the transaction to close shortly, subject to customary closing conditions. Hannes Mühleisen and Mark Raasveldt, who created DuckDB and co-founded DuckLabs, will continue leading the team and the open-source project’s technical direction as part of AWS. The DuckDB open-source project will also continue to be driven by the DuckLabs team, remain open source under the independent Foundation (the non-profit that oversees DuckDB), and available under the MIT license as it does today.

PythonOperator and BashOperator now available on Amazon Managed Workflows for Apache Airflow (Amazon MWAA) Serverless

PythonOperator and BashOperator Now Available on Amazon Managed Workflows for Apache Airflow (Amazon MWAA) Serverless

You can now use PythonOperator and BashOperator to run custom Python functions and shell scripts directly in the Amazon MWAA Serverless runtime, without provisioning additional infrastructure. This post walks through building a serverless pipeline that converts CSV files to JSON using a PythonOperator and verifies the output with a BashOperator.

GPU-accelerated Apache Spark with Amazon EMR and NVIDIA RTX PRO 4500 on Amazon EC2 G7 instances runs up to 3.7x faster

GPU-accelerated Apache Spark with Amazon EMR and NVIDIA RTX PRO 4500 on Amazon EC2 G7 instances runs up to 3.7x faster

Amazon EMR on EKS now runs Apache Spark up to 3.7x faster on Amazon EC2 G7 instances with NVIDIA RTX PRO 4500 Blackwell GPUs than on comparable CPU instances, with no changes to existing Spark code. See the TPC-DS benchmark results, the cost comparison, and how to get started.

Introducing AWS Glue 6.0 for faster and more cost-effective data integration

Introducing AWS Glue 6.0 for faster and more cost-effective data integration

AWS Glue 6.0 is now available, lowering AWS Glue pricing by 30%, adding an AWS optimized build of Apache Spark 4.1, and introducing Apache Iceberg V3 capabilities suitable for enterprise adoption. This post covers the key capabilities and performance benefits, with code examples to help you get started.

Long-term system tables retention in Amazon Redshift with Amazon S3 Tables

Long-term system tables retention in Amazon Redshift with Amazon S3 Tables

Amazon Redshift system table integration with Amazon S3 Tables automatically delivers your system table logs to Amazon S3 Tables in Apache Iceberg format. You can retain this data well beyond the 7-day limit for compliance, auditing, and cross-warehouse observability, without custom ETL pipelines or cluster resource consumption.

Amazon MSK simplifies configuring custom domain names

Amazon MSK simplifies configuring custom domain names

With Amazon MSK, you can now configure custom domain names for provisioned clusters using a single configuration property that works identically on ZooKeeper and KRaft. Define the domain once and Amazon MSK applies it across every broker, so custom domain names keep working as the cluster scales.

Mutual TLS and SSL certificate authentication for Amazon MQ for RabbitMQ

Mutual TLS and SSL certificate authentication for Amazon MQ for RabbitMQ

Learn how to add certificate-based identity verification to Amazon MQ for RabbitMQ. This post explains SSL certificate authentication for passwordless login through the EXTERNAL SASL mechanism and mutual TLS (mTLS) for two-way certificate verification, highlights the key rabbitmq.conf settings, and helps you decide which approach fits your compliance requirements.