AWS Big Data Blog
Category: Amazon Athena
How Novo Nordisk built distributed data governance and control at scale
This is a guest post co-written with Jonatan Selsing and Moses Arthur from Novo Nordisk. This is the second post of a three-part series detailing how Novo Nordisk, a large pharmaceutical enterprise, partnered with AWS Professional Services to build a scalable and secure data and analytics platform. The first post of this series describes the […]
Perform upserts in a data lake using Amazon Athena and Apache Iceberg
Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable). Apache Iceberg is an open table format for data lakes that manages large collections of files as […]
Build a transactional data lake using Apache Iceberg, AWS Glue, and cross-account data shares using AWS Lake Formation and Amazon Athena
Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. It allows you to access diverse data sources, build business intelligence dashboards, build AI and machine learning (ML) models to provide customized customer experiences, and accelerate the curation of new datasets for consumption by adopting a modern data […]
Visualize Confluent data in Amazon QuickSight using Amazon Athena
This is a guest post written by Ahmed Saef Zamzam and Geetha Anne from Confluent. Businesses are using real-time data streams to gain insights into their company’s performance and make informed, data-driven decisions faster. As real-time data has become essential for businesses, a growing number of companies are adapting their data strategy to focus on […]
Interact with Apache Iceberg tables using Amazon Athena and cross account fine-grained permissions using AWS Lake Formation
We recently announced support for AWS Lake Formation fine-grained access control policies in Amazon Athena queries for data stored in any supported file format using table formats such as Apache Iceberg, Apache Hudi and Apache Hive. AWS Lake Formation allows you to define and enforce database, table, and column-level access policies to query Iceberg tables […]
Extend geospatial queries in Amazon Athena with UDFs and AWS Lambda
Amazon Athena is a serverless and interactive query service that allows you to easily analyze data in Amazon Simple Storage Service (Amazon S3) and 25-plus data sources, including on-premises data sources or other cloud systems using SQL or Python. Athena built-in capabilities include querying for geospatial data; for example, you can count the number of […]
Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena
Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats. However, as data processing at scale solutions grow, organizations need […]
Improve productivity by using keyboard shortcuts in Amazon Athena query editor
Amazon Athena is a serverless, interactive analytics service built on open-source frameworks, supporting open-table and file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and over 25 data sources, including on-premises […]
Access Amazon Athena in your applications using the WebSocket API
In this post, we present a solution that can integrate with your front-end application to query data from Amazon S3 using an Athena synchronous API invocation. With this solution, you can add a layer of abstraction to your application on direct Athena API calls and promote the access using the WebSocket API developed with Amazon API Gateway. The query results are returned back to the application as Amazon S3 presigned URLs.
Use Apache Iceberg in a data lake to support incremental data processing
Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. It adds tables to compute engines including Spark, Trino, PrestoDB, Flink, and Hive using a high-performance table format that works just like a SQL table. Iceberg has […]