AWS News Blog
Category: Analytics
Amazon MSK Serverless Now Generally Available–No More Capacity Planning for Your Managed Kafka Clusters
Today we are making Amazon MSK Serverless generally available to help you reduce even more the operational overhead of managing an Apache Kafka cluster by offloading the capacity planning and scaling to AWS. In May 2019, we launched Amazon Managed Streaming for Apache Kafka (Amazon MSK) to help our customers stream data using Apache Kafka. […]
New – Create and Manage EMR Clusters and Spark Jobs with Amazon SageMaker Studio
Today, we’re very excited to offer three new enhancements to our Amazon SageMaker Studio service. As of now, users of SageMaker Studio can create, terminate, manage, discover, and connect to Amazon EMR clusters running within a single AWS account and in shared accounts across an organization—all directly from SageMaker Studio. Furthermore, SageMaker Studio Notebook users […]
Amazon Kinesis Data Streams On-Demand – Stream Data at Scale Without Managing Capacity
Today we are launching Amazon Kinesis Data Streams On-demand, a new capacity mode. This capacity mode eliminates capacity provisioning and management for streaming workloads. Kinesis Data Streams is a fully-managed, serverless service for real-time processing of streamed data at a massive scale. Kinesis Data Streams can take any amount of data, from any number of […]
Introducing Amazon Redshift Serverless – Run Analytics At Any Scale Without Having to Manage Data Warehouse Infrastructure
We’re seeing the use of data analytics expanding among new audiences within organizations, for example with users like developers and line of business analysts who don’t have the expertise or the time to manage a traditional data warehouse. Also, some customers have variable workloads with unpredictable spikes, and it can be very difficult for them […]
AWS Lake Formation – General Availability of Cell-Level Security and Governed Tables with Automatic Compaction
A data lake can help you break down data silos and combine different types of analytics into a centralized repository. You can store all of your structured and unstructured data in this repository. However, setting up and managing data lakes involve a lot of manual, complicated, and time-consuming tasks. AWS Lake Formation makes it easy […]
Announcing AWS Data Exchange for APIs: Find, Subscribe to, and Use Third-party APIs with Consistent Authentication
Data is at the center of many processes and products, whether it’s a large-scale dataset used to train machine learning models, a relational database, or an API-based integration. AWS Data Exchange lets you discover, subscribe to, and use hundreds of file-based datasets via Amazon Simple Storage Service (Amazon S3) offered by third parties such as […]
New – AWS Data Exchange for Amazon Redshift
Back in 2019 I told you about AWS Data Exchange and showed you how to Find, Subscribe To, and Use Data Products. Today, you can choose from over 3600 data products in ten categories: In my introductory post I showed you how could subscribe to data products and then download the data sets into an […]
Introducing Amazon Redshift Query Editor V2, a Free Web-based Query Authoring Tool for Data Analysts
When it comes to manipulating and analyzing relational data, Structured Query Language (SQL) has been an international standard since 1986, a couple of years before I was born. And yet, it sometimes takes hours to get access to a new database or data warehouse, configure credentials or single sign-on, download and install multiple desktop libraries […]