Architecture

System blueprints for scalable batch processing, real-time data streaming, and AI-powered analytics query interfaces.

Batch Data Platform

Data Sources→Airflow→Data Lake→dbt→Warehouse→BI
Batch Data Platform diagram

Streaming Data Platform

Event Producers→Kafka→Consumers→Warehouse→Real-time Analytics
Streaming Data Platform diagram

AI Data Query System

User Query→LLM→SQL Generator→Database→Response
AI Data Query System diagram

Operational Metrics Snapshot

Batch ThroughputTB/day
Stream Processing Lag< 2s
Query Success Rate99.9%
Pipeline ReliabilitySLA

ETL / ELT Architecture Playground

Drag stack components into architecture stages to model a pipeline and preview demo performance metrics.

ETL transforms data before loading into the warehouse.

Ingestion→Orchestration→Storage→Transformation→Warehouse→Serving / BI

What Changed

ETL View

  • • Transformation occurs before the warehouse load.
  • • Good for strict upstream data quality control.
  • • Can increase pipeline latency due to pre-load processing.
Ingestion

Drop stack blocks here

Orchestration

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Storage

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Transformation

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Warehouse

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Serving / BI

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Complete all stages in the selected ETL flow to view demo performance metrics (0/6 configured).

Demo model uses synthetic scoring for architecture comparison only.

Blocks deployed: 0. Use the mode switch to compare ETL vs ELT architecture behavior.