Real-time insights, simplified
with SQL stream processing
In today’s fast-paced business environment, organizations need to make real-time decisions based on the most up-to-date insights. To fully leverage the potential of your data, it is essential to process it as soon as it arrives, rather than waiting until it has been stored.
Continuously ingest and process data from OLTP databases and message queues, and deliver results to downstream data warehouses and data lakes.Learn More Streaming ETL Use cases
Real-time monitoring, alerting, automation, and data analytics capabilities. Continuously perform data stream analytics and maintain fresh results for BI and application access.Learn More Streaming Analytics Use cases
Get started on stream processing
in just few a minutes
- Fully managed service
- Unparalleled user experience
- Reduced costs
- Distributed engine built for stream processing
- Cloud-native architecture for elasticity and cost efficiency
- Seamless integration with the PostgreSQL ecosystem
Trusted by Data driven organizations
to leverage continuous insights on live data
We’ve got lots of helpful tips
and resources for you
On the Way to Democratize Stream Processing on the Cloud: RisingWave Cloud Roadmap 2023 Edition
The core objective of RisingWave Cloud has always been crystal clear: to democratize stream processing on the cloud. We know everyone has been eagerly anticipating the next steps in the development of RisingWave Cloud, and this article will reveal them to you.
Use RisingWave to Process and Transform Abandoned Cart Events
Abandoned cart data refers to the data collected when customers begin making purchases on an e-commerce platform by adding items to their shopping carts but do not complete the transaction. This topic will introduce the idea of using RisingWave to process and transform abandoned cart data from multiple sources.