AWS Big Data Blog

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.

Query Amazon S3 Tables from Amazon EMR Trino using the Iceberg REST endpoint

Query Amazon S3 Tables from Amazon EMR Trino using the Iceberg REST endpoint

Learn how to query Amazon S3 Tables from Trino on Amazon EMR using the Apache Iceberg REST catalog endpoint. This post shows how to deploy the integration with AWS CloudFormation, configure the Trino catalog, and run SQL to create, query, and manage Apache Iceberg tables.

Building medallion architecture with Iceberg materialized views in Amazon SageMaker

Building medallion architecture with Iceberg materialized views in Amazon SageMaker

With Apache Iceberg materialized views in Amazon SageMaker, you can build a Bronze, Silver, and Gold medallion architecture as three SQL statements. This declarative approach folds transformation, orchestration, and incremental processing into per-layer definitions, with no ETL jobs, orchestrators, or change-data-capture code to maintain.

Build a dynamic streaming data lake with Apache Iceberg and Apache Flink

Build a dynamic streaming data lake with Apache Iceberg and Apache Flink

Learn how to build a dynamic streaming data lake on Amazon Managed Service for Apache Flink that adapts to new event types and schema changes without stopping the pipeline, using Apache Iceberg’s Dynamic Iceberg Sink for per-record table routing and automatic schema evolution.

Observing and evaluating production agents using OpenSearch Agent Health

Observing and evaluating production agents using OpenSearch Agent Health

Learn how to observe and evaluate production AI agents by combining an agent running on AWS with OpenSearch Agent Health. This post walks through deploying an agent and its observability pipeline to AWS, then using Agent Health to explore traces and run evaluations that measure and improve agent quality over time.

Accelerate Apache Spark debugging on Amazon EMR with AWS DevOps Agent

Accelerate Apache Spark debugging on Amazon EMR with AWS DevOps Agent

Extend AWS DevOps Agent to investigate Apache Spark failures on Amazon EMR. This post shows how to register the Apache Spark Troubleshooting Agent for Amazon EMR as a custom MCP capability provider over AWS PrivateLink, so a single agent chat session diagnoses a failing Spark job from an Amazon CloudWatch alarm to a line-numbered root cause.

Deliver real-time data to streaming tables for Apache Iceberg with Amazon Kinesis Data Streams

Deliver real-time data to streaming tables for Apache Iceberg with Amazon Kinesis Data Streams

Amazon Kinesis Data Streams now supports streaming tables, a fully managed capability that continuously delivers your streaming data as queryable Apache Iceberg tables on Amazon S3 Tables. Streaming tables reduce data delivery costs to S3 Tables by up to 50% compared to self-managed alternatives and reduce downstream query costs by up to 30% through intelligent inline compaction that eliminates the small file problem. You need no custom applications, no self-managed compute, and no operational overhead.

Measuring and improving search quality with Amazon OpenSearch Service

Measuring and improving search quality with Amazon OpenSearch Service

Most teams struggle to answer a deceptively simple question: is my search returning relevant results? This post shows how to capture User Behavior Insights (UBI) data on Amazon OpenSearch Service and use Search Relevance Workbench (SRW) to turn those signals into relevance judgments and evaluate search quality.

Integrate Amazon Redshift and IAM Identity Center with enhanced VPC routing

Integrate Amazon Redshift and IAM Identity Center with enhanced VPC routing

Amazon Redshift now supports AWS IAM Identity Center authentication on clusters and workgroups that use enhanced VPC routing. Create two interface VPC endpoints to give your users single sign-on with their corporate credentials while keeping all authentication traffic on the AWS private network.

Build a real-time event pipeline with Spark Real-Time Mode on AWS Glue 6.0

Build a real-time event pipeline with Spark Real-Time Mode on AWS Glue 6.0

With AWS Glue 6.0, you can build real-time, near-real-time, and batch data pipelines on a single platform. Using a financial market-risk example, learn how to flag high-risk trades with sub-second latency using Spark Real-Time Mode, store heterogeneous pricing vectors with Apache Iceberg v3 Variant columns, and run batch analytics with Arrow-native UDFs.

Razor Group’s journey to a modern data lakehouse on AWS

Razor Group’s journey to a modern data lakehouse on AWS

Razor Group, one of Europe’s leading ecommerce aggregators managing 250+ brands, migrated from always-on Amazon Redshift clusters to an open lakehouse on Apache Iceberg, Amazon S3 Tables, and Apache Spark. Learn the architectural decisions, the five-phase migration, and the results: 65% faster P95 queries and a 63% infrastructure cost reduction.