Category: Launch

We now have a public preview of two integrations between Amazon Simple Storage Service (Amazon S3) Vectors and Amazon OpenSearch Service that give you more flexibility in how you store and search vector embeddings. In this post, we walk through this seamless integration, providing you with flexible options for vector search implementation.

Amazon SageMaker has announced an integration with Amazon QuickSight, bringing together data in SageMaker seamlessly with QuickSight capabilities like interactive dashboards, pixel perfect reports and generative business intelligence (BI)—all in a governed and automated manner. In this post, we walk through the complete process of integrating Amazon QuickSight with Amazon SageMaker Unified Studio, demonstrating how teams can move from raw data to published dashboards in a secure and governed environment.

With OpenSearch version 2.19, Amazon OpenSearch Service now supports hardware-accelerated enhanced latency and throughput for binary vectors. In this post, we discuss the improvements these advanced processors provide to your OpenSearch workloads, and how it can help you lower your total cost of ownership (TCO).

Today, we’re excited to introduce a new unified scheduling feature that simplifies this process. SageMaker Unified Studio allows you to create ETL flows using a visual interface and write SQL analytics queries using query books. In this post, we walk through how to schedule your visual ETL flows and query books with just a few clicks, explore the underlying architecture, and demonstrate how this feature can streamline your data workflow automation.

Today, we’re launching a new visual interface for OpenSearch Ingestion that makes it simple to create and manage your data pipelines from the AWS Management Console. With this new feature, you can build pipelines in minutes without writing complex configurations manually. In this post, we walk through how these new features work and how you can use them to accelerate your data ingestion projects.

Amazon EMR has introduced new features for instance fleets that address critical challenges in big data operations. This post explores how these innovations improve cluster resilience, scalability, and efficiency, enabling you to build more robust data processing architectures on AWS.

Amazon SageMaker Unified Studio is an integrated development environment (IDE) for data, analytics, and AI. Discover your data and put it to work using familiar AWS tools to complete end-to-end development workflows, including data analysis, data processing, model training, generative AI app building, and more, in a single governed environment. This post demonstrates how SageMaker Unified Studio unifies your analytic workloads.

Amazon OpenSearch Service launches a modernized operational analytics experience that can provide comprehensive observability spanning multiple data sources, so that you can gain insights from OpenSearch and other integrated data sources in one place. The launch also introduces OpenSearch Workspaces that provides tailored experience for popular use cases and supports access control, so that you can create a private space for your use case and share it only to your collaborators.

Amazon DataZone now launched authentication support through the  Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more. This integration empowers data users to access and analyze governed data within Amazon DataZone using familiar tools, boosting both productivity and flexibility.

Today, we are excited to announce an enhancement to the Amazon MWAA integration with the Airflow REST API. This improvement streamlines the ability to access and manage your Airflow environments and their integration with external systems, and allows you to interact with your workflows programmatically. The Airflow REST API facilitates a wide range of use cases, from centralizing and automating administrative tasks to building event-driven, data-aware data pipelines. In this post, we discuss the enhancement and present several use cases that the enhancement unlocks for your Amazon MWAA environment.