Streaming Lakehouse - RisingWave: Open-Source Streaming Database - RisingWave: Open-Source Streaming Database

Modern Lakehouse, Engineered for Streaming Data.

Stream, compact, and analyze real-time data in your Apache Iceberg lakehouse with PostgreSQL compatibility

Trusted by 1,000+ Data-Driven Organizations

to harness continuous insights from both live and historical data.

Trusted by 1,000+ Data-driven Organisations to harness continuous insights from both live and historical data.

Discover Why Businesses Rely on RisingWave for Ingesting and Transforming Streaming Data into Lakehouses

RisingWave helps teams handle real-time data transformations directly as it's ingested into data lake or warehouse. Instead of juggling complex pipelines, you can process data continuously and make it ready for analysis right away. It's fast, reliable, and works with the tools you already use.

70%

Lower Infrastructure Costs

10x

Productivity

100x

Faster Transformation

Optimized to Maximize Efficiency with Apache Iceberg

Apache Iceberg is the gold standard for open table formats, and RisingWave is purpose-built to support it seamlessly. Our team actively contributes to and leverages a Rust-based native Iceberg interface, delivering 3x faster performance for direct reading and writing compared to JVM-based big data systems like Spark and Flink. RisingWave integrates with various catalog types and runs effortlessly across any environment, including AWS, GCP, Azure, and self-hosted deployments.

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Stream, Compact, Analyze. All-In-One Experience.

RisingWave goes beyond real-time ETL/ELT for lakehouses—it also compacts data and delivers high-performance lake analytics. No vendor lock-in—your Iceberg lake is yours, and we help you integrate seamlessly with the open data ecosystem.

Ingesting and Transforming Streaming Data in Real Time

Continuously track and capture data changes from Kafka or database Change Data Capture (CDC) streams. Transform updates on the fly and seamlessly sync them to your data lakehouse—whether Iceberg or Delta Lake—ensuring fresh, query-ready data in real time, without the complexity of batch processing.

Compact Parquet Files Whenever Needed

Continuously compact Parquet files in Iceberg to optimize performance and minimize storage overhead. Maintain a fast, efficient, and query-ready data lakehouse—eliminating the complexity of manual maintenance.

Run Lake Analytics Using the Same Engine

Run high-performance analytics directly on your Iceberg lake without the need for external query engines. With built-in support for SQL-based querying, RisingWave enables seamless real-time insights, ad-hoc exploration, and complex analytics—all while ensuring optimal storage and compute efficiency. Whether you're processing streaming updates or historical data, RisingWave makes Iceberg analytics fast, efficient, and scalable.

Rich Set of Connectors

RisingWave offers purpose-built streaming connectors equipped with built-in intelligence to detect back pressure, enabling efficient data ingestion from numerous sources in a decentralized manner.

Composable Data Pipelines

Live data has short shelf life. Incremental updates are triggered automatically in RisingWave to guarantee always fresh insights letting users get the most value of their data sets.

Incremental Processing for Ultra Low Latency

RisingWave makes data pipelines composable, allowing tables and views generated by one query to be seamlessly used as inputs for downstream queries.

Native Data Lake Formats Support

Interoperability is a core design principle of RisingWave. As Iceberg and Delta increasingly become the de facto standards for data lakehouse table formats, RisingWave provides robust read and write support for both.

Explore how RisingWave can help with Real-Time ETL/ELT

Join our experts for an in-depth exploration, gain valuable insights into real-time data transformation and see how RisingWave can simplify your ETL process before kicking off your free trial with confidence.

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Time Travel Queries in RisingWave: Unlocking Historical Insights from Streaming Data

In traditional databases, retrieving historical data often involves snapshotting, manual versioning, or audit logging. However, RisingWave provides a built-in way to access past states of a table using Time Travel Queries. This feature is particularl...

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Streaming As-Of Joins in RisingWave: Real-Time Event Matching for Time-Series Data

In many real-time applications, such as financial trading, risk analytics, and IoT monitoring, timestamps in data streams from different sources may not match exactly. To process these streams effectively, we often need to join them by matching the n...

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Building Real-Time Graph Analysis Pipeline with RisingWave and PuppyGraph

Real-time data analysis is becoming crucial across various applications, from financial risk management and social networking to recommendation systems and the Internet of Things. While traditional analytics provides timely insights into dynamic chan...

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