RisingWave is a streaming-first data platform. It offers a unified experience for real-time data ingestion, stream processing, low-latency serving, and Apache Iceberg™ management.
New: SQL Generator Tool! Need help writing SQL? Try our interactive SQL Assistant to generate CREATE SOURCE, CREATE TABLE, CREATE SINK, and Iceberg table statements with ease.
RisingWave integrates real-time stream processing and low-latency serving in a single system. It continuously ingests data from streaming and batch sources, performs incremental computations across streams and tables with end-to-end freshness under 100 ms. Materialized views can be served directly within RisingWave with 10–20 ms p99 query latency, or delivered to downstream systems.
Iceberg lakehouse ingestion, transformation, and management
RisingWave treats Apache Iceberg™ as a first-class citizen. It directly hosts and manages the Iceberg REST catalog, allowing users to create and operate Iceberg tables through a PostgreSQL-compatible interface. RisingWave supports two write modes: Merge-on-Read (MoR) and Copy-on-Write (CoW), to suit different ingestion and query patterns. It also provides built-in table maintenance capabilities, including compaction, small-file optimization, vacuum, and snapshot cleanup, ensuring efficient and consistent data management without external tools or pipelines.Plug: Nimtable is an observability tool developed by RisingWave for easily exploring and managing Iceberg tables.
RisingWave stores tables, materialized views, and internal states of stream processing jobs in object storage (e.g., S3, GCS, MinIO), providing:
High performance: Optimized for complex queries, including joins and time windowing, without the need for complex state management.
Fast recovery: Restores from system failures within seconds.
Dynamic scaling: Instantly adjusts resources to handle workload spikes.
Beyond caching hot data in memory, RisingWave supports elastic disk cache, a powerful performance optimization that uses local disks or EBS for efficient data caching. This minimizes access to object storage like S3, lowering processing latency and cutting object store access costs.
RisingWave natively integrates with Apache Iceberg™, enabling continuous ingestion of streaming data into Iceberg tables. It can also read directly from Iceberg, perform automatic compaction, and maintain table health over time. Since Iceberg is an open table format, results are accessible by other query engines — making storage not only cost-efficient, but interoperable by design.
For business-level monitoring where every transaction or event matters. RisingWave continuously evaluates event streams from trading, payments, and fraud detection systems to identify anomalies, policy violations, or performance issues, and triggers alerts within seconds.
For event-driven analytics and operational pipelines that join and enrich multiple data streams such as trades, orders, quotes, or reference data in real time. RisingWave supports multi-way joins, schema evolution, deduplication, and automatic handling of late or out-of-order events.
For high-frequency telemetry and device data in connected environments such as logistics, energy, and manufacturing. RisingWave aggregates sensor readings, computes rolling metrics, and streams processed telemetry to monitoring dashboards or AI models for anomaly detection and optimization.
For real-time lakehouse architectures built on open formats such as Apache Iceberg. RisingWave continuously ingests data from Postgres, Kafka, and other operational systems, performs transformations, compacts small files, manages schema evolution, and writes data into Iceberg tables for unified analytics and long-term retention.
