Best-in-Class Event Streaming
for Agents, Apps, and Analytics
for Agents, Apps, and Analytics
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Customer Story
Kaito powers real-time analytics for 300 million users. One data engineer built 1,000+ streaming dashboards in just 2 weeks using RisingWave.
The Challenge
Kaito's previous infrastructure relied on complex Java and Python code running on Amazon Glue, with Redis and Cassandra for serving results. The system could not scale elastically, required significant engineering effort for each new dashboard, and struggled to maintain 24/7 uptime for their global user base.
Each new dashboard required significant engineering effort to build and maintain. With 300 million users depending on real-time crypto analytics, the multi-system architecture created operational fragility and slowed product iteration.
The Solution
RisingWave replaced Kaito's multi-system stack with a single PostgreSQL-compatible streaming database. Materialized views replaced the need for Redis and Cassandra as serving layers, and elastic scaling on Google Kubernetes Engine enabled automatic resource adjustment.
SQL-based development made the platform accessible to any data engineer. Built-in state management eliminated external dependencies, and a single cluster now runs all 1,000+ materialized views with sub-millisecond query latency.
Results
Kaito deployed 1,000+ materialized views on a single cluster, all built in just 2 weeks by a single data engineer. Sub-millisecond query latency and 24/7 availability serve their 300 million users, with plans for 1,000+ additional streaming jobs.
| Metric | Before | After (RisingWave) |
|---|---|---|
| Streaming dashboards | Manual effort each | 1,000+ on one cluster |
| Time to deploy | Months | 2 weeks |
| Engineers required | Team | 1 data engineer |
| Query latency | Variable | Sub-millisecond |
| Serving layer | Redis + Cassandra | Built-in (MVs) |
| Scaling | Manual | Elastic on GKE |
Build streaming dashboards in days, not months.
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