AWS Big Data Blog

In this post, we explore the process of integrating Amazon Keyspaces and Amazon OpenSearch Service using AWS Lambda and Amazon OpenSearch Ingestion to enable advanced search capabilities. The content includes a reference architecture, a step-by-step guide on infrastructure setup, sample code for implementing the solution within a use case, and an AWS Cloud Development Kit (AWS CDK) application for deployment.

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 […]

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 […]

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 […]

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 […]

Business leaders and data analysts use near-real-time transaction data to understand buyer behavior to help evolve products. The primary challenge businesses face with near-real-time analytics is getting the data prepared for analytics in a timely manner, which can often take days. Companies commonly maintain entire teams to facilitate the flow of data from ingestion to […]

Now, at Amazon Redshift, we are announcing the general availability of multi-data warehouse writes through data sharing. This new capability allows you to achieve better performance for extract, transform, and load (ETL) workloads by using different warehouses of different types and sizes based on your workload needs.

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Furthermore, they are adopting security models that require access to the data lake […]

Many organizations use identity providers (IdPs) to authenticate users, manage their attributes, and group memberships for secure, efficient, and centralized identity management. You might be modernizing your data architecture using Amazon Redshift to enable access to your data lake and data in your data warehouse, and are looking for a centralized and scalable way to […]

Monitoring data pipelines in real time is critical for catching issues early and minimizing disruptions. AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics, which provide valuable insights into your data integration pipelines built on AWS Glue. However, you might need to track key performance indicators across multiple […]