Amazon Redshift Streaming Ingestion

Generate near real time insights through streaming data ingestion into your data warehouse and data visualizations

Get started with Amazon Redshift Streaming Ingestion

Benefits

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.

How it works

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Use cases

Customer Quotes

”LiveMe is a live broadcast app that attracts more than 1 million anchors from over 220 countries. Our app powers more than 100k hours of live broadcasts every day. We use Amazon Redshift's streaming ingestion and other Amazon services for risk control over users' financial activity such as recharge, refund, and rewards. With Amazon Redshift, we are able to view risk control reports and data in near real time, instead of on an hourly basis. This significantly improved our business efficiency.”

PengBo Yang, CTO, Joyme (parent company of LiveMe)

“We found Amazon Redshift streaming extremely easy to use since everything is in SQL. Using the power of Redshift to analyze event data in near real-time enables us to reduce complexity and save costs.”

Ben Shin, Director, Match Group