# risingwavelabs/risingwave

Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.

Repository: https://github.com/risingwavelabs/risingwave
Canonical: https://ross.abutalabs.com/products/risingwave
Homepage: https://go.risingwave.com/slack
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: database, stream-processing, rust, postgresql, kafka, materialized-view, data-engineering, apache-iceberg, etl-pipeline, event-streaming, webhook
Last push: 2026-08-26T19:24:08+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 98, longevity 100
- inputs: {"age_days": 1678, "days_push": 7, "days_rel": 16, "gap_med": 10, "n_releases_24m": 58}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 9290, forks 825 (observed 2026-08-28T04:10:30.316364+00:00)

## What it is
RisingWave is an event streaming platform that continuously ingests data from databases, event streams, and webhooks, processes it incrementally, and serves fresh results at low latency. It replaces the traditional Debezium + Kafka + Flink + serving database stack with a single PostgreSQL-compatible system.

## Use cases
- stream processing for real-time analytics
- ingest CDC from PostgreSQL and MySQL
- process Kafka event streams with SQL
- serve fresh data to AI agents at low latency
- replace Kafka and Flink with a single system
- ingest webhooks and transform events in real time
- build materialized views over streaming data

## When to choose
- you need low-latency serving of continuously updated data
- you want to consolidate CDC, streaming, and serving into one system
- your team prefers SQL over building Flink pipelines
- you're building real-time backends for agentic AI applications

## When to avoid
- you only need simple batch ETL without real-time requirements
- you already have a mature Kafka/Flink stack with deep operational expertise
- your workload is purely transactional OLTP

## Facets
- artifact type: service
- maturity: active
- function: streaming, etl, database, message-queue
- domain: databases, artificial-intelligence
- platform: rust, cloud, self-hosted
- tags: stream-processing, materialized-views, cdc, postgresql-compatible, event-streaming, agentic-ai, sql, data-engineering, real-time, docker, kubernetes

## Member repositories
- risingwavelabs/risingwave (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:30.316364+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:22:33.325052+00:00, confidence not recorded.
  - readme: https://github.com/risingwavelabs/risingwave (fetched 2026-08-28T04:10:30.316364+00:00, sha ea8d50b4cfd1)
- Data as of 2026-08-30T08:39:29.467469+00:00.