AWS Big Data Blog

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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. However, altering schema and table partitions in traditional data lakes can be a disruptive and time-consuming task, requiring renaming or recreating entire tables and reprocessing large datasets. […]

How BMO improved data security with Amazon Redshift and AWS Lake Formation

This post is cowritten with Amy Tseng, Jack Lin and Regis Chow from BMO. BMO is the 8th largest bank in North America by assets. It provides personal and commercial banking, global markets, and investment banking services to 13 million customers. As they continue to implement their Digital First strategy for speed, scale and the […]

Introducing Terraform support for Amazon OpenSearch Ingestion

Today, we are launching Terraform support for Amazon OpenSearch Ingestion. Terraform is an infrastructure as code (IaC) tool that helps you build, deploy, and manage cloud resources efficiently. OpenSearch Ingestion is a fully managed, serverless data collector that delivers real-time log, metric, and trace data to Amazon OpenSearch Service domains and Amazon OpenSearch Serverless collections. […]

Introducing Amazon MWAA support for Apache Airflow version 2.8.1

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that makes it straightforward to set up and operate end-to-end data pipelines in the cloud. Organizations use Amazon MWAA to enhance their business workflows. For example, C2i Genomics uses Amazon MWAA in their data platform to orchestrate the validation […]

Empowering data-driven excellence: How the Bluestone Data Platform embraced data mesh for success

This post is co-written with Toney Thomas and Ben Vengerovsky from Bluestone. In the ever-evolving world of finance and lending, the need for real-time, reliable, and centralized data has become paramount. Bluestone, a leading financial institution, embarked on a transformative journey to modernize its data infrastructure and transition to a data-driven organization. In this post, […]

Simplify data streaming ingestion for analytics using Amazon MSK and Amazon Redshift

Towards the end of 2022, AWS announced the general availability of real-time streaming ingestion to Amazon Redshift for Amazon Kinesis Data Streams and Amazon Managed Streaming for Apache Kafka (Amazon MSK), eliminating the need to stage streaming data in Amazon Simple Storage Service (Amazon S3) before ingesting it into Amazon Redshift. Streaming ingestion from Amazon […]

Combine AWS Glue and Amazon MWAA to build advanced VPC selection and failover strategies

AWS Glue is a serverless data integration service that makes it straightforward to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. AWS Glue customers often have to meet strict security requirements, which sometimes involve locking down the network connectivity allowed to the job, or running inside […]

Build an analytics pipeline that is resilient to schema changes using Amazon Redshift Spectrum

You can ingest and integrate data from multiple Internet of Things (IoT) sensors to get insights. However, you may have to integrate data from multiple IoT sensor devices to derive analytics like equipment health information from all the sensors based on common data elements. Each of these sensor devices could be transmitting data with unique […]

Simplify authentication with native LDAP integration on Amazon EMR

Many companies have corporate identities stored inside identity providers (IdPs) like Active Directory (AD) or OpenLDAP. Previously, customers using Amazon EMR could integrate their clusters with Active Directory by configuring a one-way realm trust between their AD domain and the EMR cluster Kerberos realm. For more details, refer to Tutorial: Configure a cross-realm trust with […]

Multi-Warehouse ETL Architecture. Two workloads--a Purchase History ETL job ingesting 10M rows nightly and users running 25 read queries per hour--using a 32 RPU serverless workgroup to read from and write to the database Customer DB. It shows a separate workload--a Web Interactions ETL job ingesting 400M rows/hour--using a separate 128 RPU serverless workgroup to write to the database Customer DB.

Improve your ETL performance using multiple Redshift warehouses for writes (Preview)

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. Thousands of customers use Amazon Redshift read data sharing to enable instant, granular, and fast data access across Redshift provisioned clusters and serverless workgroups. This allows you to scale your read workloads to […]