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Real-Time Unified Data Platform

A visual, low-code platform for managing streaming and batch pipelines. It efficiently handles real-time synchronization of massive, multi-source data to build a modern real-time lakehouse

Efficient, Real-Time, Low-Code SaaS Solution

Built on LakeSoul, the leading domestic lakehouse storage framework, this solution ingests massive multi-source data into the lakehouse in real time, supports whole-database synchronization, automatic schema evolution, and automatic new-table discovery. It interconnects seamlessly with diverse business scenarios to enable intelligent data applications and maximize the value of data.

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Feature-Rich

Ingests multi-source data from MySQL, Oracle, Kafka, and more into the lakehouse in real time. Once ingested, data can be analyzed and computed in real time, and snapshot queries are supported. Downstream, it connects to a variety of BI and AI engines to unlock the value of data.

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Efficient and Stable

High-speed updates on cloud object storage with T+0 real-time computation and rapid feedback on results. Automatic checkpointing delivers exactly-once data ingestion.

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Simple and Fast

Deploys easily on public and private clouds, Hadoop, and Kubernetes clusters. A web UI for configuration and development simplifies the process and makes it easy to get started.

A Complete Lakehouse Ecosystem from Data Sources to Applications

A modern ELT data architecture. The platform connects to a wide range of upstream data sources for real-time synchronization, powering real-time data warehousing, reporting, machine learning, OLAP, and other downstream applications — helping enterprises advance their digital transformation.

Resolve the mismatch between diverse data sources and traditional big data architectures, enabling efficient, flexible, secure, and reliable data use

Broad Scenario Coverage

Databases, log files, and other data sources can be ingested into the lakehouse in real time for analytics, machine learning sample generation, and other BI and AI applications.

Efficient and Automated

Automatically synchronizes whole databases, creates tables, and applies schema changes without manual intervention, reducing the burden on developers.

Low Cost

Separated compute and storage, elastic scaling, and a unified stream-batch architecture eliminate redundant data pipelines. All data is stored on cloud object storage to reduce costs.

Real-Time Analytics on Operational Databases

With a few configurations for your online data sources, whole-database synchronization and real-time ingestion start automatically. New tables are detected and schema changes are synchronized without manual operations. Operational data is ingested into the lakehouse in real time and flows seamlessly into BI reports and dashboards, so key business metrics are always up to date to support decision-making.

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