Category: Serverless

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset. Many organizations today are using AWS Glue to build ETL pipelines that bring data […]

June 2023: This post was reviewed and updated to support MFA setup instructions. Amazon Redshift Serverless makes it easy to run and scale analytics in seconds without the need to set up and manage data warehouse clusters. With Redshift Serverless, users such as data analysts, developers, business professionals, and data scientists can get insights from […]

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tens of thousands of customers use Amazon Redshift to process exabytes of data per […]

This is a guest post co-written by Maik Leuthold and Nick Harmening from BMW Group. The BMW Group is headquartered in Munich, Germany, where the company oversees 149,000 employees and manufactures cars and motorcycles in over 30 production sites across 15 countries. This multinational production strategy follows an even more international and extensive supplier network. Like many automobile companies across the world, the […]

Amazon OpenSearch Serverless is a serverless option of Amazon OpenSearch Service that makes it easy for you to run large-scale search and analytics workloads without having to configure, manage, or scale OpenSearch clusters. It automatically provisions and scales the underlying resources to deliver fast data ingestion and query responses for even the most demanding and […]

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) […]

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. This post […]

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.

Amazon EMR Serverless is a serverless option in Amazon EMR that makes it simple to run applications using open-source analytics frameworks such as Apache Spark and Hive without configuring, managing, or scaling clusters. At AWS re:Invent 2022, we announced support for running serverless Spark and Hive workloads with AWS Graviton2 (Arm64) on Amazon EMR Serverless. […]

Amazon EMR Serverless allows you to run open-source big data frameworks such as Apache Spark and Apache Hive without managing clusters and servers. With EMR Serverless, you can run analytics workloads at any scale with automatic scaling that resizes resources in seconds to meet changing data volumes and processing requirements. EMR Serverless automatically scales resources up […]