AWS Big Data Blog

Category: Learning Levels

Amazon MWAA best practices for managing Python dependencies

Customers with data engineers and data scientists are using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) as a central orchestration platform for running data pipelines and machine learning (ML) workloads. To support these pipelines, they often require additional Python packages, such as Apache Airflow Providers. For example, a pipeline may require the Snowflake provider […]

Amazon DataZone enhances data discovery with advanced search filtering

Amazon DataZone, a fully managed data management service, helps organizations catalog, discover, analyze, share, and govern data between data producers and consumers. We are excited to announce the introduction of advanced search filtering capabilities in the Amazon DataZone business data catalog. With the improved rendering of glossary terms, you can now navigate large sets of […]

Implement disaster recovery with Amazon Redshift

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. The objective of a disaster recovery plan is […]

Architecture Overview

Build a real-time streaming generative AI application using Amazon Bedrock, Amazon Managed Service for Apache Flink, and Amazon Kinesis Data Streams

Data streaming enables generative AI to take advantage of real-time data and provide businesses with rapid insights. This post looks at how to integrate generative AI capabilities when implementing a streaming architecture on AWS using managed services such as Managed Service for Apache Flink and Amazon Kinesis Data Streams for processing streaming data and Amazon Bedrock to utilize generative AI capabilities. We include a reference architecture and a step-by-step guide on infrastructure setup and sample code for implementing the solution with the AWS Cloud Development Kit (AWS CDK). You can find the code to try it out yourself on the GitHub repo.

Access Amazon Redshift data from Salesforce Data Cloud with Zero Copy Data Federation

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights. This data is primarily used for analytical and machine learning purposes, […]

Run Apache Spark 3.5.1 workloads 4.5 times faster with Amazon EMR runtime for Apache Spark

The Amazon EMR runtime for Apache Spark is a performance-optimized runtime that is 100% API compatible with open source Apache Spark. It offers faster out-of-the-box performance than Apache Spark through improved query plans, faster queries, and tuned defaults. Amazon EMR on EC2, Amazon EMR Serverless, Amazon EMR on Amazon EKS, and Amazon EMR on AWS […]

Image showing multiple producers and consumers each publishing to a stream-per-tenant

Stream multi-tenant data with Amazon MSK

AWS helps SaaS vendors by providing the building blocks needed to implement a streaming application with Amazon Kinesis Data Streams and Amazon Managed Streaming for Apache Kafka (Amazon MSK), and real-time processing applications with Amazon Managed Service for Apache Flink. In this post, we look at implementation patterns a SaaS vendor can adopt when using a streaming platform as a means of integration between internal components, where streaming data is not directly exposed to third parties. In particular, we focus on Amazon MSK.

Apply fine-grained access and transformation on the SUPER data type in Amazon Redshift

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tens of thousands of customers use Amazon Redshift to process exabytes of data per […]

Build multimodal search with Amazon OpenSearch Service

Multimodal search enables both text and image search capabilities, transforming how users access data through search applications. Consider building an online fashion retail store: you can enhance the users’ search experience with a visually appealing application that customers can use to not only search using text but they can also upload an image depicting a […]

Ingest and analyze your data using Amazon OpenSearch Service with Amazon OpenSearch Ingestion

In today’s data-driven world, organizations are continually confronted with the task of managing extensive volumes of data securely and efficiently. Whether it’s customer information, sales records, or sensor data from Internet of Things (IoT) devices, the importance of handling and storing data at scale with ease of use is paramount. A common use case that […]