
Power real-time analytics and data-driven applications with low-latency data preparation.
Integrate data from databases, streams, and business systems into a unified analytics pipeline.
Reduce compute and network costs with incremental data replay and CDC.
Fit into existing ODS, DW, and DWM data warehouse standards.
A scalable architecture designed for real-time analytics and large-scale data processing.

Core Warehouse: Use StarRocks for real-time analytics at the hundreds-of-terabytes scale
Real-time Ingestion: BladePipe uses CDC and stream loading for high-performance, low-latency incremental updates
DW Layer: Data is cleaned, aggregated, and combined using views or primary key tables
APP/DWM Layer: Build data services with materialized views or primary key tables based on business needs

Learn how to build a real-time lakehouse using BladePipe, Apache Paimon, and StarRocks, from architecture design to hands-on steps for ingestion, sync, and real-time analytics.


Learn what a wide table is, when to use it, and how to build wide tables to optimize complex queries and analytics with BladePipe.
