AWS News Blog

Category: AWS Glue

New — Amazon SageMaker Data Wrangler Supports SaaS Applications as Data Sources

Data fuels machine learning. In machine learning, data preparation is the process of transforming raw data into a format that is suitable for further processing and analysis. The common process for data preparation starts with collecting data, then cleaning it, labeling it, and finally validating and visualizing it. Getting the data right with high quality […]

New – Amazon Redshift Integration with Apache Spark

Apache Spark is an open-source, distributed processing system commonly used for big data workloads. Spark application developers working in Amazon EMR, Amazon SageMaker, and AWS Glue often use third-party Apache Spark connectors that allow them to read and write the data with Amazon Redshift. These third-party connectors are not regularly maintained, supported, or tested with […]

New AWS Glue 4.0 – New and Updated Engines, More Data Formats, and More

AWS Glue is a scalable, serverless tool that helps you to accelerate the development and execution of your data integration and ETL workloads. Today we are launching Glue 4.0, with updated engines, support for additional data formats, Ray support, and a lot more. Before I dive in, just a word about versioning. Unlike most AWS […]

Announcing AWS Glue DataBrew – A Visual Data Preparation Tool That Helps You Clean and Normalize Data Faster

To be able to run analytics, build reports, or apply machine learning, you need to be sure the data you’re using is clean and in the right format. That’s the data preparation step that requires data analysts and data scientists to write custom code and do many manual activities. First, you need to look at […]

AWS Glue version 2.0 featuring 10x faster job start times and 1-minute minimum billing duration

AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. Glue is “serverless” – you don’t need to provision or manage any resources and you only pay for resources when Glue is actively running. AWS Glue version 2.0 is […]

New – Serverless Streaming ETL with AWS Glue

When you have applications in production, you want to understand what is happening, and how the applications are being used. To analyze data, a first approach is a batch processing model: a set of data is collected over a period of time, then run through analytics tools. To be able to react quickly, you can […]

New for Amazon Redshift – Data Lake Export and Federated Query

A data warehouse is a database optimized to analyze relational data coming from transactional systems and line of business applications. Amazon Redshift is a fast, fully managed data warehouse that makes it simple and cost-effective to analyze data using standard SQL and existing Business Intelligence (BI) tools. To get information from unstructured data that would […]