AWS Big Data Blog

Category: AWS Glue

Interactively develop your AWS Glue streaming ETL jobs using AWS Glue Studio notebooks

Enterprise customers are modernizing their data warehouses and data lakes to provide real-time insights, because having the right insights at the right time is crucial for good business outcomes. To enable near-real-time decision-making, data pipelines need to process real-time or near-real-time data. This data is sourced from IoT devices, change data capture (CDC) services like […]

Set up and monitor AWS Glue crawlers using the enhanced AWS Glue UI and crawler history

A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. AWS Glue and AWS Lake Formation make it easy to build, secure, and manage data […]

Set up federated access to Amazon Athena for Microsoft AD FS users using AWS Lake Formation and a JDBC client

Tens of thousands of AWS customers choose Amazon Simple Storage Service (Amazon S3) as their data lake to run big data analytics, interactive queries, high-performance computing, and artificial intelligence (AI) and machine learning (ML) applications to gain business insights from their data. On top of these data lakes, you can use AWS Lake Formation to […]

Introducing AWS Glue interactive sessions for Jupyter

Interactive Sessions for Jupyter is a new notebook interface in the AWS Glue serverless Spark environment. Starting in seconds and automatically stopping compute when idle, interactive sessions provide an on-demand, highly-scalable, serverless Spark backend to Jupyter notebooks and Jupyter-based IDEs such as Jupyter Lab, Microsoft Visual Studio Code, JetBrains PyCharm, and more. Interactive sessions replace […]

AWS Glue Python shell now supports Python 3.9 with a flexible pre-loaded environment and support to install additional libraries

AWS Glue is the central service of an AWS modern data architecture. It is a serverless data integration service that allows you to discover, prepare, and combine data for analytics and machine learning. AWS Glue offers you a comprehensive range of tools to perform ETL (extract, transform, and load) at the right scale. AWS Glue […]

How NerdWallet uses AWS and Apache Hudi to build a serverless, real-time analytics platform

This is a guest post by Kevin Chun, Staff Software Engineer in Core Engineering at NerdWallet. NerdWallet’s mission is to provide clarity for all of life’s financial decisions. This covers a diverse set of topics: from choosing the right credit card, to managing your spending, to finding the best personal loan, to refinancing your mortgage. […]

Introducing AWS Glue Flex jobs: Cost savings on ETL workloads

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Typically, these […]

Best practices to optimize cost and performance for AWS Glue streaming ETL jobs

AWS Glue streaming extract, transform, and load (ETL) jobs allow you to process and enrich vast amounts of incoming data from systems such as Amazon Kinesis Data Streams, Amazon Managed Streaming for Apache Kafka (Amazon MSK), or any other Apache Kafka cluster. It uses the Spark Structured Streaming framework to perform data processing in near-real […]

How Epos Now modernized their data platform by building an end-to-end data lake with the AWS Data Lab

Epos Now provides point of sale and payment solutions to over 40,000 hospitality and retailers across 71 countries. Their mission is to help businesses of all sizes reach their full potential through the power of cloud technology, with solutions that are affordable, efficient, and accessible. Their solutions allow businesses to leverage actionable insights, manage their […]

Use SQL queries to define Amazon Redshift datasets in AWS Glue DataBrew

July 2023: This post was reviewed for accuracy. In the post Data preparation using Amazon Redshift with AWS Glue DataBrew, we saw how to create an AWS Glue DataBrew job using a JDBC connection for Amazon Redshift. In this post, we show you how to create a DataBrew profile job and a recipe job using […]