risingwavelabs/risingwave

Deployment

For self-hosted: - Docker Compose - Kubernetes with Helm - Kubernetes with Operator

Ingest from any source

All sources are unified under the same SQL interface. Streams and tables can be joined freely.

• Webhooks: HTTP-based event ingestion from SaaS applications and external systems
• Database changes: native CDC from PostgreSQL, MySQL, and others via transaction log reading
• Event streams: Kafka, Pulsar, Kinesis, and other message brokers
• Historical data: batch ingestion from S3, data warehouses, and other storage systems

Use cases

• Monitoring and alerting: continuous evaluation of streaming metrics against thresholds
• Feature stores: batch and streaming features computed over the same pipeline, served from the same system
• Live dashboards: materialized views updated incrementally, no scheduled refreshes
• Real-time enrichment: live events joined with historical reference data in-flight, before delivery downstream
• Streaming lakehouses: continuous, exactly-once ingestion into open-format tables with automated compaction and snapshot management

🌊 Event Streaming for Agentic AI

RisingWave is an event streaming platform for agentic AI. It continuously ingests data from databases, event streams, and webhooks, processes it incrementally, and serves fresh results at low latency, replacing the traditional event streaming stack (e.g., Debezium + Kafka + Flink + serving DB) with a single system.