AWS Big Data Blog

Category: Analytics

Migrate terabytes of data quickly from Google Cloud to Amazon S3 with AWS Glue Connector for Google BigQuery

This blog post was last updated July, 2022 to update the new version of the connector and details on how to push down queries to Google BigQuery. The cloud is often seen as advantageous for data lakes because of better security, faster time to deployment, better availability, more frequent feature and functionality updates, more elasticity, […]

Doing data preparation using on-premises PostgreSQL databases with AWS Glue DataBrew

Today, with AWS Glue DataBrew, data analysts and data scientists can easily access and visually explore any amount of data across their organization directly from their Amazon Simple Storage Service (Amazon S3) data lake, Amazon Redshift data warehouse, and Amazon Aurora and Amazon Relational Database Service (Amazon RDS) databases. Customers can choose from over 250 […]

Orchestrate an Amazon EMR on Amazon EKS Spark job with AWS Step Functions

At re:Invent 2020, we announced the general availability of Amazon EMR on Amazon EKS, a new deployment option for Amazon EMR that allows you to automate the provisioning and management of open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With Amazon EMR on EKS, you can now run Spark applications alongside other […]

Build a real-time streaming application using Apache Flink Python API with Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics is now expanding its Apache Flink offering by adding support for Python. This is exciting news for many of our customers who use Python as their primary language for application development. This new feature enables developers to build Apache Flink applications in Python using serverless Kinesis Data Analytics. With Kinesis Data […]

Introducing Auto-Tune in Amazon ES

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Today we announced Auto-Tune in Amazon OpenSearch Service, an innovation undertaken to automatically optimize resources in Elasticsearch clusters to improve its performance and availability. Auto-Tune gives us a unique opportunity of applying our learnings from operating clusters at cloud scale […]

Build a serverless tracking pixel solution in AWS

Let’s describe the typical use case where a tracking pixel solution, also known as a web beacon, might help you: Analyzing web traffic is critical to understanding user behavior in order to improve their experience. Let’s think about a company—Example Company Hotels—that embeds a piece of HTML into a high-traffic, third-party website ( to have […]

The following graph shows that the minimum throughput achieved with the persistent HFile

Amazon EMR 6.2.0 adds persistent HFile tracking to improve performance with HBase on Amazon S3

Apache HBase is an open-source, NoSQL database that you can use to achieve low latency random access to billions of rows. Starting with Amazon EMR 5.2.0, you can enable HBase on Amazon Simple Storage Service (Amazon S3). With HBase on Amazon S3, the HBase data files (HFiles) are written to Amazon S3, enabling data lake […]

Best Western slashes analytics costs, improves operations worldwide using Amazon QuickSight

This is a guest blog post by Best Western Hotels and Resorts. In their own words, “Best Western Hotels & Resorts is an award-winning global network of hotels located in over 100 countries and territories that offers accommodations for all types of travelers.” With 18 brands and varied ownership structures across geographies, Best Western Hotel […]

Automate dynamic mapping and renaming of column names in data files using AWS Glue: Part 1

A common challenge ETL and big data developers face is working with data files that don’t have proper name header records. They’re tasked with renaming the columns of the data files appropriately so that downstream application and mappings for data load can work seamlessly. One example use case is while working with ORC files and […]

Automate dynamic mapping and renaming of column names in data files using AWS Glue: Part 2

In Part 1 of this two-part post, we looked at how we can create an AWS Glue ETL job that is agnostic enough to rename columns of a data file by mapping to column names of another file. The solution focused on using a single file that was populated in the AWS Glue Data Catalog […]