AWS Big Data Blog

Category: Storage

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.

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.

Enable cross-cloud analytics with Amazon S3 Tables and Google BigQuery, Part 1: IAM-based access control

Enable cross-cloud analytics with Amazon S3 Tables and Google BigQuery, Part 1: IAM-based access control

Your Google BigQuery users need to query data that lives in Amazon S3 Tables on AWS without copying it across clouds. This post shows how to connect BigQuery to Amazon S3 Tables through the AWS Glue Iceberg REST Catalog using IAM-based access control, so you keep one governed dataset and query it live from BigQuery.

Enable cross-cloud analytics with Amazon S3 Tables and Google BigQuery, Part 2: access control with Lake Formation

Enable cross-cloud analytics with Amazon S3 Tables and Google BigQuery, Part 2: access control with Lake Formation

In Part 2 of this series, connect Google BigQuery to Amazon S3 Tables using AWS Lake Formation credential vending. Lake Formation manages fine-grained permissions and issues short-lived, scoped credentials to external engines, so you can centrally govern which teams and query engines read your Iceberg tables on AWS without managing IAM policies for every consumer.

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.

Fresher insights, faster decisions: talabat’s near-real-time analytics across AWS and Google Cloud

Fresher insights, faster decisions: talabat’s near-real-time analytics across AWS and Google Cloud

Leading everyday app across the Middle East and North Africa, talabat, built a hybrid multi-cloud lakehouse that keeps a single Apache Iceberg copy of streaming data on Amazon S3 Tables while letting Google BigQuery query it in place, eliminating cross-cloud data duplication and schema-synchronization overhead.

How Autodesk migrated 2.3 billion documents to Amazon OpenSearch Service using Migration Assistant and intelligent routing

This post walks through how Autodesk re-architected a single-index Elasticsearch 7.1.1 domain on Amazon OpenSearch Service into four multi-index OpenSearch Service domains, using Migration Assistant for Amazon OpenSearch Service and a routing layer that directs each query to the shards that hold the data for that query.

Deliver Apache Kafka data to streaming tables for Apache Iceberg with Amazon MSK Express brokers

Deliver Apache Kafka data to streaming tables for Apache Iceberg with Amazon MSK Express brokers

Announcing delivery to streaming tables on Apache Iceberg for Amazon MSK Express brokers, a fully managed capability that continuously materializes your Kafka streaming data as queryable Iceberg tables on Amazon S3 Tables. No connectors, Flink jobs, or custom consumers to manage, and no code to write.

Build a contract compliance search system with Amazon OpenSearch

In this post, you build a contract compliance search system that combines semantic search with semantic highlighting in Amazon OpenSearch Service. You deploy the solution using two AWS CloudFormation stacks, test it with synthetic contract documents, and see how a single query surfaces both the right contracts and the right clauses within them.

Automate creating AWS Glue Data Catalog views with AWS SDK for data mesh use case

This post shows you how to use the Catalog objects API CreateTable() to programmatically create ATHENA and SPARK dialects using cross-account IAM definer roles, and how to add the ATHENA dialect programmatically for the views that were created earlier with only SPARK dialect.