Category: Amazon Athena

This post is co-written with Amit Gilad, Alex Dickman and Itay Takersman from Cloudinary.  Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. Data-driven decisions lead to more effective responses to unexpected events, increase innovation and allow […]

Many organizations use external identity providers (IdPs) such as Okta or Microsoft Azure Active Directory to manage their enterprise user identities. These users interact with and run analytical queries across AWS analytics services. To enable them to use the AWS services, their identities from the external IdP are mapped to AWS Identity and Access Management […]

Apache Hudi was originally developed by Uber in 2016 to bring to life a transactional data lake that could quickly and reliably absorb updates to support the massive growth of the company’s ride-sharing platform. Apache Hudi is now widely used to build very large-scale data lakes by many across the industry. Today, Hudi is the […]

We’re excited to announce the launch of the Apache Iceberg on AWS technical guide. Whether you are new to Apache Iceberg on AWS or already running production workloads on AWS, this comprehensive technical guide offers detailed guidance on foundational concepts to advanced optimizations to build your transactional data lake with Apache Iceberg on AWS.

This is a guest post co-authored with Kanehito Miyake, Engineer at Fujitsu Japan.  Fujitsu Limited was established in Japan in 1935. Currently, we have approximately 120,000 employees worldwide (as of March 2023), including group companies. We develop business in various regions around the world, starting with Japan, and provide digital services globally. To provide a […]

In this post, we discuss how to implement bucketing on AWS data lakes, including using Athena CTAS statement and AWS Glue for Apache Spark. We also cover bucketing for Apache Iceberg tables.

Many organizations operate data lakes spanning multiple cloud data stores. This could be for various reasons, such as business expansions, mergers, or specific cloud provider preferences for different business units. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics […]

Many organizations around the world rely on the use of physical assets, such as vehicles, to deliver a service to their end-customers. By tracking these assets in real time and storing the results, asset owners can derive valuable insights on how their assets are being used to continuously deliver business improvements and plan for future […]

Customers today may struggle to implement proper access controls and auditing at the user level when multiple applications are involved in data access workflows. The key challenge is to implement proper least-privilege access controls based on user identity when one application accesses data on behalf of the user in another application. It forces you to […]

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. However, altering schema and table partitions in traditional data lakes can be a disruptive and time-consuming task, requiring renaming or recreating entire tables and reprocessing large datasets. […]