AWS Big Data Blog

Category: Technical How-to

In-place version upgrades for applications on Amazon Managed Service for Apache Flink now supported

Managed Service for Apache Flink is a fully managed, serverless experience in running Apache Flink applications, and now supports Apache Flink 1.18.1, the latest released version of Apache Flink at the time of writing. In this post, we explore in-place version upgrades, a new feature offered by Managed Service for Apache Flink. We provide guidance on getting started and offer detailed insights into the feature. Later, we deep dive into how the feature works and some sample use cases.

Use AWS Data Exchange to seamlessly share Apache Hudi datasets

Apache Hudi was originally developed by Uber in 2016 to bring to life a transactional data lake that could quickly and reliably absorb updates to support the massive growth of the company’s ride-sharing platform. Apache Hudi is now widely used to build very large-scale data lakes by many across the industry. Today, Hudi is the […]

Achieve peak performance and boost scalability using multiple Amazon Redshift serverless workgroups and Network Load Balancer

As data analytics use cases grow, factors of scalability and concurrency become crucial for businesses. Your analytic solution architecture should be able to handle large data volumes at high concurrency and without compromising speed, thereby delivering a scalable high-performance analytics environment. Amazon Redshift Serverless provides a fully managed, petabyte-scale, auto scaling cloud data warehouse to […]

Governing data in relational databases using Amazon DataZone

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone is a fully managed data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across Amazon Web Services (AWS), on premises, and on third-party […]

Analyze more demanding as well as larger time series workloads with Amazon OpenSearch Serverless 

In today’s data-driven landscape, managing and analyzing vast amounts of data, especially logs, is crucial for organizations to derive insights and make informed decisions. However, handling this data efficiently presents a significant challenge, prompting organizations to seek scalable solutions without the complexity of infrastructure management. Amazon OpenSearch Serverless lets you run OpenSearch in the AWS […]

Detect and handle data skew on AWS Glue

October 2024: This post was reviewed and updated for accuracy. AWS Glue is a fully managed, serverless data integration service provided by Amazon Web Services (AWS) that uses Apache Spark as one of its backend processing engines (as of this writing, you can use Python Shell or Spark). Data skew occurs when the data being […]

Use your corporate identities for analytics with Amazon EMR and AWS IAM Identity Center

To enable your workforce users for analytics with fine-grained data access controls and audit data access, you might have to create multiple AWS Identity and Access Management (IAM) roles with different data permissions and map the workforce users to one of those roles. Multiple users are often mapped to the same role where they need […]

Orchestrate an end-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift Serverless with Amazon MWAA

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. Apache Airflow is an open source tool used to programmatically author, schedule, and monitor sequences of processes and tasks, referred to as workflows. […]