![Amazon Redshift](https://cdn.sanity.io/images/97bpcflt/production/762f7800546d2c1ffae9fa808fdf1d1ffa7226e7-162x200.png?bg=0fff&w=80&fit=crop&dpr=2&fm=webp&h=99)
![Amazon Kinesis](https://cdn.sanity.io/images/97bpcflt/production/1465705d5ab83bed326dc74baba381f54bc549ce-168x200.png?bg=0fff&w=80&fit=crop&dpr=2&fm=webp&h=95)
Integrate your Amazon Redshift Data Warehouse with Amazon Kinesis
Don't go through the pain of direct integration. RudderStack’s Reverse ETL connection makes it easy to send data from your Amazon Redshift Data Warehouse to Amazon Kinesis and all of your other cloud tools.With Rudderstack, integration between Amazon Redshift source and Amazon Kinesis is simple. Set up a Amazon Redshift source source and start sending data.
Pricing Amazon Redshift source and Amazon Kinesis can vary based on the way they charge. Check out our pricing page for more info. Or give us a try for FREE.
Timing can vary based on your tech stack and the complexity of your data needs for Amazon Redshift source and Amazon Kinesis.
Yes, RudderStack streamlines the integration and management of your connection between Amazon Redshift & Amazon Kinesis, but you check out our guide on How To Send Data From Snowflake to Amazon Kinesis to learn how to connect the tools manually.
Amazon Kinesis enables you to ingest, buffer and process streaming data in real-time. It can handle any amount of streaming data and process data from hundreds of thousands of sources with very low latencies along with the flexibility to choose the tools that best suit the requirements of your application. Kinesis supports various data formats such as audio, video, application logs, clickstream data, and IoT data. It provides unique streaming services to ingest and leverage this data to perform machine learning as well as advanced analytics.
Amazon Redshift is the world's fastest cloud data warehouse. It allows you to handle large analytical workloads with best-in-class performance, speed, and efficiency. With Redshift, you don't have to worry about the scale of your data or the cost of running queries on them.