AWS Big Data Blog

Customers can harness sophisticated orchestration capabilities through the open-source tool Apache Airflow. Airflow can be installed on Amazon EC2 instances or can be dockerized and deployed as a container on AWS container services. Alternatively, customers can also opt to leverage Amazon Managed Workflows for Apache Airflow (MWAA). Amazon MWAA is a fully managed service that […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data and gain actionable insights in real time with Apache Flink. Apache Flink is an […]

Our customers use Apache Hive on Amazon EMR for large-scale data analytics and extract, transform, and load (ETL) jobs. Amazon EMR Hive uses Apache Tez as the default job execution engine, which creates Directed Acyclic Graphs (DAGs) to process data. Each DAG can contain multiple vertices from which tasks are created to run the application […]

Customers are migrating data warehouses to Amazon Redshift because it’s fast, scalable, and cost-effective. However, data warehouse migration projects can be complex and challenging. In this post, I help you understand the common drivers of data warehouse migration, migration strategies, and what tools and services are available to assist with your migration project. Let’s first […]

Amazon Athena is a serverless interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) using standard SQL, and you only pay for the amount of data scanned by your queries. If you use SQL to analyze your business on a daily basis, you may find yourself repeatedly […]

Many customers already manage user identities through identity providers (IdPs) for single sign-on access. With an IdP such as Active Directory Federation Services (AD FS), you can set up federated access to Amazon Redshift clusters as a mechanism to control permissions for the database objects by business groups. This provides a seamless user experience, and centralizes the governance […]

This is the fifth in a series of posts. We’re excited to share dozens of new features to automate your schema conversion; preserve your investment in existing scripts, reports, and applications; accelerate query performance; and potentially simplify your migrations from legacy data warehouses to Amazon Redshift. Check out the all the posts in this series: […]

This blog is only meant to be used as a reference for backing up and restoring data for an Amazon MSK cluster. AWS does not offer any support for it. You can use Apache Kafka to run your streaming workloads. Kafka provides resiliency to failures and protects your data out of the box by replicating […]

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS designed hardware and machine […]

Apache Kafka is well known for its performance and tunability to optimize for various use cases. But sometimes it can be challenging to find the right infrastructure configuration that meets your specific performance requirements while minimizing the infrastructure cost. This post explains how the underlying infrastructure affects Apache Kafka performance. We discuss strategies on how […]