Category: AWS Lake Formation

In this two-part series, we show how to integrate custom applications or data processing engines with Lake Formation using the third-party services integration feature. In this post, we dive deep into the required Lake Formation and AWS Glue APIs. We walk through the steps to enforce Lake Formation policies within custom data applications. As an example, we present a sample Lake Formation integrated application implemented using AWS Lambda.

In this two-part series, we show how to integrate custom applications or data processing engines with Lake Formation using the third-party services integration feature. In this post, we explore how to deploy a fully functional web client application, built with JavaScript/React through AWS Amplify (Gen 1), that uses the same Lambda function as the backend. The provisioned web application provides a user-friendly and intuitive way to view the Lake Formation policies that have been enforced.

In this post, we discuss how to implement fine-grained access control in EMR Serverless using Lake Formation. With this integration, organizations can achieve better scalability, flexibility, and cost-efficiency in their data operations, ultimately driving more value from their data assets.

This post explores how BMW implemented AWS Lake Formation’s fine-grained access control (FGAC) in the Cloud Data Hub and how this saves them up to 25% on compute and storage costs. By using AWS Lake Formation fine-grained access control capabilities, BMW has transparently implemented finer data access management within the Cloud Data Hub. The integration of Lake Formation has enabled data stewards to scope and grant granular access to specific subsets of data, reducing costly data duplication.

After careful consideration, we have made the decision to end support for Governed Tables, effective December 31, 2024, to focus on open source transactional table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. This decision stems from customer preference for these open source solutions, which offer ACID-compliant transactions, compaction, time travel, and other features previously provided by Governed Tables.

In this post, we explore a solution using AWS Lake Formation and AWS IAM Identity Center to address the complex challenges of managing and governing legacy data during digital transformation. We demonstrate how enterprises can effectively preserve historical data while enforcing compliance and maintaining user entitlements. This solution enables your organization to maintain robust audit trails, enforce governance controls, and provide secure, role-based access to data.

Capital Fund Management (CFM) is an alternative investment management company based in Paris with staff in New York City and London. CFM takes a scientific approach to finance, using quantitative and systematic techniques to develop the best investment strategies. In this post, we share how we built a well-governed and scalable data engineering platform using Amazon EMR for financial features generation.

The AWS Glue Data Catalog now enhances managed table optimization of Apache Iceberg tables by automatically removing data files that are no longer needed. Along with the Glue Data Catalog’s automated compaction feature, these storage optimizations can help you reduce metadata overhead, control storage costs, and improve query performance. Iceberg creates a new version called […]

Glue Data Catalog views is a new feature of the AWS Glue Data Catalog that customers can use to create a common view schema and single metadata container that can hold view-definitions in different dialects that can be used across engines such as Amazon Redshift and Amazon Athena. In this blog post, we will show how you can define and query a Data Catalog view on top of open source table formats such as Iceberg across Athena and Amazon Redshift. We will also show you the configurations needed to restrict access to the underlying database and tables. To follow along, we have provided an AWS CloudFormation template.

In this post, we cover how to enable trusted identity propagation with AWS IAM Identity Center, Amazon Redshift, and AWS Lake Formation residing on separate AWS accounts and set up cross-account sharing of an S3 data lake for enterprise identities using AWS Lake Formation to enable analytics using Amazon Redshift. Then we use Amazon QuickSight to build insights using Redshift tables as our data source.