From de9aef3e4898da15a2546bb2f08999c62d85ff81 Mon Sep 17 00:00:00 2001 From: Yingjun Wu Date: Mon, 5 Aug 2024 16:04:14 -0700 Subject: [PATCH] chore: Update README.md (#17909) Co-authored-by: emile-00 <106993396+emile-00@users.noreply.github.com> Co-authored-by: emile-00 --- README.md | 21 +++++++++------------ 1 file changed, 9 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index f4fb81afa675..bf50ae208a97 100644 --- a/README.md +++ b/README.md @@ -54,11 +54,18 @@ -RisingWave is a Postgres-compatible streaming database engineered to provide the simplest and most cost-efficient approach for processing, analyzing, and managing real-time event streaming data. - +RisingWave is a Postgres-compatible SQL engine engineered to provide the simplest and most cost-efficient approach for processing, analyzing, and managing real-time event streaming data. ![RisingWave](https://github.com/risingwavelabs/risingwave/assets/41638002/10c44404-f78b-43ce-bbd9-3646690acc59) +## When to use RisingWave? +RisingWave can ingest millions of events per second, continuously join live data streams with historical tables, and serve ad-hoc queries in real-time. Typical use cases include, but are not limited to: + +* **Streaming analytics**: Perform streaming analytics and build live dashboards with data freshness under one second, ideal for stock trading, sports betting, IoT monitoring, and more. +* **Event-driven applications**: Develop monitoring and alerting applications for fraud detection, anomaly detection, and more. +* **Real-time ETL pipelines**: Ingest data from different sources, perform enrichment queries, and deliver results to downstream systems. +* **Feature stores**: Transform both batch and streaming data into ML features using the same codebase. + ## Try it out in 60 seconds @@ -126,16 +133,6 @@ RisingWave is fundamentally a database that **extends beyond basic streaming dat * Schema change * Processing of semi-structured data -## In-production use cases -Within your data stack, RisingWave can assist with: - -* Processing and transforming event streaming data in real time -* Offloading event-driven queries (e.g., materialized views, triggers) from operational databases -* Performing real-time ETL (Extract, Transform, Load) -* Supporting real-time feature stores - -Read more at [use cases](https://risingwave.com/use-cases/). RisingWave is extensively utilized in real-time applications such as monitoring, alerting, dashboard reporting, machine learning, among others. It has already been adopted in fields such as financial trading, manufacturing, new media, logistics, gaming, and more. Check out [customer stories](https://risingwave.com/resources/?filter=customer-stories). - ## Community Looking for help, discussions, collaboration opportunities, or a casual afternoon chat with our fellow engineers and community members? Join our [Slack workspace](https://risingwave.com/slack)!