Amazon Redshift: AWS Services Integration

Break through data silos and gain real-time and predictive insights on all your data

Benefits of Amazon Redshift

Break through data silos with federated querying, which accesses your data in place from operational databases, data lakes, and data warehouses. Enable your organizations across accounts and Regions to work on shared, transactionally consistent data without data movement or data copying. Find, subscribe to, and query third-party datasets with zero ETL, cutting time to get to comprehensive insights. Connect this data to your favorite BI tool like Amazon QuickSight or to your application using data APIs for dashboarding, line of business analysis, and business decision making.
Run real-time analytics on your transactional data with Amazon Aurora zero-ETL integration with Amazon Redshift, making data available in the warehouse for analytics within seconds of it being written into Amazon Aurora. Support for autocopy simplifies and automates file ingestion from Amazon Simple Storage Service (S3). With Redshift Streaming Ingestion capabilities, you can directly ingest any amount of streaming data with high throughput and low latency for improving customer responsiveness, operations, and delivering real-time insights.
Developers can run Apache Spark applications directly on Amazon Redshift data from AWS Analytics services, such as Amazon EMR and AWS Glue. Amazon Redshift integration for Apache Spark expands the data warehouse for a broader set of rich analytics, enhancing performance and security for Apache Spark-based applications. With Amazon Redshift ML, run billions of predictions with simple SQL commands with native integration into Amazon SageMaker, initiating on data science within your data warehouse. Amazon Redshift’s integration with Amazon Forecast further assists data scientists and analysts conducting sophisticated ML forecasting using SQL.

Use cases

Generate Apache Spark code using AWS Glue Studio or Amazon EMR to transform and write data in Amazon Redshift.

Replicate data from multiple Amazon Aurora databases into a single data warehouse in near real time. Analyze customer behavior and help your applications and business react quickly to customer opportunities.

Ingest files from Amazon S3 continuously and when available, with automatic COPY operations and no custom coding or manual ingestion activities.
The average customer visits dozens of websites in a single session, yet marketers typically analyze only their own websites. Assess each customer’s footprint and behaviors with authorized clickstream data ingested into the warehouse.
Get a visual analysis of your data by connecting BI tools to Amazon Redshift and accessing all your data. With tools like Amazon QuickSight you can ask questions of the data in natural language, creating visually appealing dashboards, and leading to faster and more simplified business decision making.

Customers

  • Stripe
  • “Millions of companies use Stripe’s software and APIs to accept payments, send payouts, and manage their businesses online. Access to their Stripe data via leading data warehouses like Amazon Redshift has been a top request from our customers. Our customers needed secure, fast, and integrated analytics at scale without building complex data pipelines or moving and copying data around. With Stripe Data Pipeline for Amazon Redshift, we’re helping our customers set up a direct and reliable data pipeline in a few clicks. Stripe Data Pipeline enables our customers to automatically share their complete, up-to-date Stripe data with their Amazon Redshift data warehouse, and take their business analytics and reporting to the next level.”

    Tony Petrossian, Head of Engineering, Revenue and Financial Management, Stripe

  • Adobe
  • Adobe empowers everyone, from individuals and small businesses to government agencies and global brands, to create and deliver exceptional digital experiences. 

    “Adobe’s mission is to change the world through digital experiences, and in today’s world, that means having analytics that can deliver both deep and real-time insights. As an Amazon Aurora customer, we are excited for Amazon Aurora support for zero-ETL integration with Amazon Redshift, which will provide our growing Acrobat Sign customer base with new insights and faster analytics performance as their usage increases—all without the need for ongoing maintenance for our own teams.”

    Jack Lull, Principal Scientist, Adobe Acrobat Sign

  • Qlik
  • Qlik helps enterprises around the world move faster, work smarter, and lead the way forward with an end-to-end solution for getting value out of data.

    "Today, Qlik’s Data Integration delivers real-time, analytics-ready data into streaming and cloud platforms such as data warehouses and data lakes. By capturing transactional data seconds after it is written and replicating it in the data warehouse, Amazon Aurora zero-ETL integration with Amazon Redshift meets the growing customer need for real-time availability of transactional data for analytics workloads. We look forward to integrating with the new capability to enhance the value we bring to our customers to enable time-sensitive insights."

    Itamar Ankorion, Senior Vice President for Technology Alliances, Qlik

  • Infor
  • Infor is a global leader in business cloud software and industry-specific enterprise resource planning solutions.

    “Infor is a global leader in business cloud software and industry-specific enterprise resource planning solutions. At Infor, we use AWS to build and deploy modern tools to help our customers transform their business and accelerate innovation. This includes a new managed data warehouse service for our customers' industry cloud data, which will help our customers make faster decisions with advanced analytics and ML. We are excited for Amazon Aurora to support zero-ETL integration with Amazon Redshift, which will reduce our operational burden by making transactional data from Amazon Aurora available in Amazon Redshift in near real time. Now, we can benefit from the performance of Amazon Aurora as our relational database management system while easily leveraging the analytics and ML capabilities in Amazon Redshift for our new managed data warehouse service.“

    Jim Plourde, Senior Vice President for Cloud Services, Infor

  • Jobcase
  • “Jobcase has several models in production using Amazon Redshift ML. Each model performs billions of predictions in minutes directly on our Redshift data warehouse, with no data pipelines required. With Redshift ML, we have evolved to model architectures that generate a 5-10% improvement in member and member engagement rates across several different email template types, with no inference costs.”

    Mike Griffin, EVP Optimization and Analytics, Jobcase

Resources

Blog

AWS announces Amazon Aurora zero-ETL integration with Amazon Redshift (Generally Available)

Blog

AWS announces Amazon Aurora zero-ETL integration with Amazon Redshift (Public Preview)

blog

Realizing near real-time analytics with a zero-ETL future

Case Study

Jobcase scales ML workflows to support billions of daily events

Guide

Learn about Federated Querying

Blogs

Review the AWS News Blog on simple data ingestion with Amazon Redshift

Website

Learn about Amazon Redshift Streaming Ingestion

Documentation

Using Apache Iceberg tables with Amazon Redshift

Blog

How Fannie Mae built a data mesh architecture to enable self-service using Amazon Redshift data sharing