risingwavelabs/risingwave
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 3 days ago, with 225 contributors on GitHub.
Peaked at #96 in the weekly ranking the week of Mar 1, its best in the past year.
Use Cases & Benefits
- Provides an event streaming platform that ingests, processes, and serves real-time event data at scale with native Apache Iceberg support.
- Delivers ultra-low-latency stream processing combined with cost-effective, unified data management using PostgreSQL-compatible SQL and Python interfaces.
- Use for building live dashboards requiring sub-second data freshness in high-stakes environments like stock trading or IoT monitoring.
- Use for developing real-time monitoring and alerting systems for critical applications such as fraud detection and anomaly identification.
- Use for powering lakehouse architectures that continuously ingest streaming data into Apache Iceberg tables for unified analytics and governance.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
RisingWave is an enterprise-grade event streaming platform designed to offer the simplest and most cost-effective way to ingest, process, and manage real-time event data — with built-in support for the Apache Iceberg™ open table format. It provides both a Postgres-compatible SQL interface and a DataFrame-style Python interface.
RisingWave can ingest millions of events per second, continuously join and analyze live streams with historical data, serve ad-hoc queries at low latency, and manage data reliably in Apache Iceberg™ tables.
To learn about other installation options, such as using a Docker image, see the quick start guide.
RisingWave delivers a unified streaming data platform that combines ultra-low-latency stream processing and Iceberg-native data management.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+161 stars over 90 days across 9 snapshot days; best day +5 on Aug 13.
Forks
862+50
Open issues
1.9K+290
Compared with peers in Data Engineering
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| vectordotdev/vector | 22.8K | — | 64 | 11 days ago |
| ThreeDotsLabs/watermill | 10.0K | — | 56 | 76 days ago |
| risingwavelabs/risingwave | 9.4K | — | 60 | 3 days ago |
| OpenDCAI/DataFlow | 8.5K | — | 54 | 10 days ago |
| Eventual-Inc/Daft | 5.8K | — | 65 | 3 days ago |
| ruc-datalab/DeepAnalyze | 4.8K | — | 15 | — |
| Category median | 8.5K | — | 56 | — |
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