AWS Big Data Blog

Category: AWS Glue

Introducing enhanced support for tagging, cross-account access, and network security in AWS Glue interactive sessions

AWS Glue interactive sessions allow you to run interactive AWS Glue workloads on demand, which enables rapid development by issuing blocks of code on a cluster and getting prompt results. This technology is enabled by the use of notebook IDEs, such as the AWS Glue Studio notebook, Amazon SageMaker Studio, or your own Jupyter notebooks. […]

How Chime Financial uses AWS to build a serverless stream analytics platform and defeat fraudsters

This is a guest post by Khandu Shinde, Staff Software Engineer and Edward Paget, Senior Software Engineering at Chime Financial. Chime is a financial technology company founded on the premise that basic banking services should be helpful, easy, and free. Chime partners with national banks to design member first financial products. This creates a more […]

Explore real-world use cases for Amazon CodeWhisperer powered by AWS Glue Studio notebooks

Many customers are interested in boosting productivity in their software development lifecycle by using generative AI. Recently, AWS announced the general availability of Amazon CodeWhisperer, an AI coding companion that uses foundational models under the hood to improve software developer productivity. With Amazon CodeWhisperer, you can quickly accept the top suggestion, view more suggestions, or […]

Operational Data Processing Framework for Modern Data Architectures

Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS has invested in native service integration with Apache Hudi and published technical contents to enable you to use Apache Hudi with AWS Glue (for example, refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started). In AWS ProServe-led customer engagements, the use cases we work on usually come with technical complexity and scalability requirements. In this post, we discuss a common use case in relation to operational data processing and the solution we built using Apache Hudi and AWS Glue.

Securely process near-real-time data from Amazon MSK Serverless using an AWS Glue streaming ETL job with IAM authentication

Streaming data has become an indispensable resource for organizations worldwide because it offers real-time insights that are crucial for data analytics. The escalating velocity and magnitude of collected data has created a demand for real-time analytics. This data originates from diverse sources, including social media, sensors, logs, and clickstreams, among others. With streaming data, organizations […]

Extracting key insights from Amazon S3 access logs with AWS Glue for Ray

This blog post presents an architecture solution that allows customers to extract key insights from Amazon S3 access logs at scale. We will partition and format the server access logs with Amazon Web Services (AWS) Glue, a serverless data integration service, to generate a catalog for access logs and create dashboards for insights.

Query your Iceberg tables in data lake using Amazon Redshift

Amazon Redshift supports querying a wide variety of data formats, such as CSV, JSON, Parquet, and ORC, and table formats like Apache Hudi and Delta. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map. With this capability, Amazon Redshift extends your petabyte-scale data warehouse to an exabyte-scale data lake on Amazon S3 in a cost-effective manner. Apache Iceberg is the latest table format that is supported by Amazon Redshift. In this post, we show you how to query Iceberg tables using Amazon Redshift, and explore Iceberg support and options.

Automate the archive and purge data process for Amazon RDS for PostgreSQL using pg_partman, Amazon S3, and AWS Glue

The post Archive and Purge Data for Amazon RDS for PostgreSQL and Amazon Aurora with PostgreSQL Compatibility using pg_partman and Amazon S3 proposes data archival as a critical part of data management and shows how to efficiently use PostgreSQL’s native range partition to partition current (hot) data with pg_partman and archive historical (cold) data in […]

Introducing AWS Glue crawler and create table support for Apache Iceberg format

Apache Iceberg is an open table format for large datasets in Amazon Simple Storage Service (Amazon S3) and provides fast query performance over large tables, atomic commits, concurrent writes, and SQL-compatible table evolution. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time […]

How Ontraport reduced data processing cost by 80% with AWS Glue

This post is written in collaboration with Elijah Ball from Ontraport. Customers are implementing data and analytics workloads in the AWS Cloud to optimize cost. When implementing data processing workloads in AWS, you have the option to use technologies like Amazon EMR or serverless technologies like AWS Glue. Both options minimize the undifferentiated heavy lifting […]