Customer Story

CVTE: 10+ Way Streaming Joins at Sub-Second Freshness

CVTE is a $30 billion electronics manufacturer. They replaced their crash-prone in-memory system with RisingWave, enabling 10+ way streaming joins with sub-second freshness.

10+
Stream Joins
<1s
Freshness
>1TB
Memory Eliminated
$30B
Market Cap

The Challenge

What was CVTE's challenge with their previous stream processor?

CVTE initially used PipelineDB and later built a custom in-memory stream processor. Both systems were single-instance only, required full recomputation on crash, consumed over 1TB of memory for complex multi-way joins, and offered poor observability into pipeline health.

No horizontal scaling was available to handle growing manufacturing data volumes, and every crash or restart meant rebuilding the entire pipeline state from scratch -- an unacceptable risk for production manufacturing systems.

The Solution

How did RisingWave solve CVTE's manufacturing streaming needs?

RisingWave introduced persistent checkpoints that eliminate recomputation on failure, decoupled compute and storage for independent scaling, Debezium CDC for seamless database ingestion, and native Grafana integration for comprehensive monitoring of all streaming pipelines.

State is stored durably rather than in memory, dramatically reducing resource requirements. The decoupled compute-storage architecture enables CVTE to scale compute and storage independently as their manufacturing data volumes grow.

Results

What results did CVTE achieve with RisingWave?

CVTE now runs 10+ way streaming joins with sub-second data freshness. The system eliminated over 1TB of memory requirements by using durable state storage, recovers from crashes without recomputation, and provides full pipeline observability through Grafana dashboards.

MetricBeforeAfter (RisingWave)
Concurrent stream joinsLimited10+ way joins
Data freshnessMinutesSub-second
Memory required>1TB in-memoryDurable state storage
Crash recoveryFull recomputationPersistent checkpoints
ArchitectureSingle-instanceHorizontally scalable
Pipeline observabilityPoorFull (Grafana)

Ready to scale your manufacturing data?

Handle complex streaming joins without the complexity.

Scale Your Manufacturing Data →
Best-in-Class Event Streaming
for Agents, Apps, and Analytics
GitHubXLinkedInSlackYouTube
Sign up for our to stay updated.