Amazon Redshift Streaming Ingestion

Process large volumes of streaming data from multiple sources with low latency and high throughput to derive insights in seconds.

Directly ingest streaming data into your data warehouse from Kinesis Data Streams and MSK without the need to stage in Amazon S3.

Perform rich analytics on streaming data within Amazon Redshift using familiar SQL. Define and build materialized views on top of streams directly. Create and manage downstream ELT pipelines by creating MV on MVs, using user-defined functions and stored procedures in Amazon Redshift.

Generate insights by visualizing your streaming data within a business intelligence solution of your choice. Build charts and other visuals within a solution like Amazon QuickSight, a unified serverless business intelligence solution with native ML integrations, to enable data driven decision making in your organization. Use machine learning powered Amazon QuickSight Q to ask conversational questions of your data and receive answers through relevant visualizations.

Increase in-game conversion, player retention, and optimize gaming experience by analyzing real-time data from gamers.

Analyze data from thousands of IoT devices and use machine learning (ML) within Amazon Redshift to improve operations, predict customer churn, and grow your business.

The average customer visits dozens of websites in a single session, yet marketers typically analyze only their own websites. Analyze authorized clickstream data ingested into the warehouse to assess your customers’ footprint and behaviors.

By accessing and analyzing streaming data from application log files and network logs, developers and engineers can conduct real-time troubleshooting, deliver better products, and alert systems for preventative measures.

Access and visualize in near real time all POS retail sales transaction data for real-time analytics, reporting, and visualization.