RisingWave Open Lake
Managed Iceberg™ Tables,
Built for Everyone
Built by the main contributors to the Apache Iceberg Rust project, RisingWave Open Lake is the easiest way to launch and scale your Apache Iceberg–based lakehouse. It brings together catalog hosting, batch and streaming ingestion, and automatic compaction — all while providing full interoperability so every query engine can truly access your data in a fresh and consistent manner. Available in open source and in our fully managed service.
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Trusted by 1,000+ Data-Driven Organizations

to harness continuous insights from both live and historical data.

Trusted by 1,000+ Data-Driven Organizations to harness continuous insights from both live and historical data.
SIEMENS
Robinhood
Tencent
Henkel
KAITO
OpenSea
PepsiCo
Laerdal
Thumbtack
neuron
Metabit Trading
CVTE
SIEMENS
Robinhood
Tencent
Henkel
KAITO
OpenSea
PepsiCo
Laerdal
Thumbtack
neuron
Metabit Trading
CVTE
Launch Your Iceberg-based Lakehouse
in 3 Simple Steps
Stop wrestling with complex catalog setups. With RisingWave's integrated hosted catalog, you can turn your object store into a streaming-ready Apache Iceberg table with just a few lines of SQL.

Ingest data from Kafka, CDC streams, or batch sources using Postgres-style SQL, and let us handle auto-compaction, schema evolution, and other challenges.
-- 1. Connect to your object store
CREATE CONNECTION my_iceberg_connection WITH (
    type = 'iceberg',
    warehouse.path = 's3://your-bucket/iceberg-stocks',
    hosted_catalog = true -- No external catalog needed!
);

-- 2. Create your Iceberg table
CREATE TABLE stock_trades (
    trade_id INT PRIMARY KEY,
    symbol STRING,
    trade_price DOUBLE,
    trade_volume INT,
    trade_time TIMESTAMP,
    trade_value DOUBLE
) ENGINE = iceberg;

-- 3. Transform streaming data and stream results into your table
CREATE MATERIALIZED VIEW stock_trades_mv AS
SELECT
  CAST(trade_id AS INT) AS trade_id,
  TRIM(symbol) AS symbol,
  CAST(price AS DOUBLE) AS trade_price,
  CAST(volume AS INT) AS trade_volume,
  CAST(trade_time AS TIMESTAMP) AS trade_time,
  price * volume AS trade_value
FROM stock_trades_src
WHERE price > 0 AND volume > 0;

INSERT INTO stock_trades
SELECT * FROM stock_trades_mv;
Out of the Box, No Floating Pieces.
Forward-thinking companies build their lakehouse foundations on Apache Iceberg. But they shouldn't suffer from assembling and managing countless moving parts. RisingWave Open Lake handles everything for you, so you can focus on building applications and running analytics.
Hosted REST Catalog
We manage open-source REST catalog services like Apache Polaris and LakeKeeper, so you avoid the hassle of running Hive Metastore or AWS Glue while keeping your Iceberg tables consistent and queryable.
Built-in Compaction Service
Continuously optimizes small files and merges equality deletes in the background using our home-grown compute engine built on Apache DataFusion. Even if your query engine doesn’t support equality deletes, it will still work with our tables because we have already applied and compacted them for you.
Best-in-class Ingestion Service
Real-time and batch ingestion from Kafka, CDC streams, and object storage. Supports schema evolution, parallel backfill, and exactly-once delivery—letting you keep your lake fresh with minimal effort.
Incremental Materialized Views
Create materialized views directly on Iceberg tables, and even build cascading ones that can be reused across multiple queries. They refresh automatically and incrementally, so your applications can concurrently access always up-to-date data.
Your Data, Your Bucket, Your Ownership
Your Data, Your Bucket, Your Ownership
Whether you’re using the open-source edition or our fully managed service, your data always stays in your own cloud VPC. No hidden storage, no surprise fees, no security or compliance worries.

RisingWave is built on open standards, so you’re free to ingest with us, query with others, or mix and match engines like Trino, Spark, and DuckDB. Your Iceberg tables stay fully portable and queryable—always.

read the documentation

Data Streaming Workloads? We’ve Heavily Optimized for Them!

Apache Iceberg wasn’t originally designed for streaming data, but we’ve fixed that once and for all! RisingWave Open Lake works beautifully for streaming. Whether your data comes from Kafka or Postgres/MySQL CDC, we take care of the hard parts: small files, equality deletes, exactly-once guarantees, backfilling, schema evolution, and more — so you don’t have to.

Data Streaming Workloads? We’ve Heavily Optimized for Them!
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.
Data Streaming Workloads? We’ve Heavily Optimized for Them!
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.
Data Streaming Workloads? We’ve Heavily Optimized for Them!
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.

Launch and Scale Your Iceberg Lakehouse with Ease
The Modern Backbone for Your
Data Streaming Workloads
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