MooseStack

In Your Stack

Moose In Your Dev Stack

Moose handles the analytical layer of your application stack. The Area Code repository contains two working implementations that show how to integrate Moose with existing applications.

User Facing Analytics (UFA)

UFA shows how to add a dedicated analytics microservice to an existing application without impacting your primary database.

UFA Implementation

View the open source repository to see the full implementation and clone it on your own machine.

Data Flow

  1. Application writes to Supabase (transactional backend)
  2. Supabase Realtime streams changes to Analytical Backend and Retrieval Backend
  3. Moose ingest pipeline syncs change events from Redpanda into ClickHouse
  4. Frontend queries analytics APIs for dashboards

Architecture Components

The UFA template demonstrates a microservices architecture with specialized components for different data access patterns:

Frontend Layer

The user interface for dashboards and application interactions

Technologies: Vite, React, TanStack Query, TanStack Router, Tailwind CSS

Transactional Backend

Handles CRUD operations and maintains application state

Technologies: Supabase, Fastify, Drizzle ORM

Retrieval Backend

Fast text search and complex queries across large datasets

Technologies: Elasticsearch + Fastify

Analytics Backend

High-performance analytical queries and aggregations

Technologies: ClickHouse + Moose OLAP, Redpanda + Moose Streaming, Moose APIs

Sync Layer

Keep data synchronized between transactional, retrieval, and analytics systems

Technologies: Supabase Realtime, Temporal + Moose Workflows

Operational Data Warehouse (ODW)

ODW shows how to build a centralized data platform that ingests from multiple sources for business intelligence and reporting.

ODW Implementation

View the open source repository to see the full implementation and clone it on your own machine.

Data Flow

  1. Sources send data to Moose ingestion endpoints
  2. Streaming functions validate and transform data
  3. Data lands in ClickHouse tables
  4. BI tools query via generated APIs or direct SQL

Architecture Components

Data Ingestion Sinks

Handles incoming data from push-based sources (webhooks, application logs) with validation and transformation

Technologies: Moose APIs, Redpanda + Moose Streaming

Connectors & ETL Pipelines

Connects to your existing databases, object storage, or third-party APIs

Technologies: Temporal + Moose Workflows

Data Warehouse

Centralized analytical database for raw and transformed data

Technologies: ClickHouse + Moose OLAP

BI Dashboard

Query interface for business intelligence and reporting

Technologies: Streamlit dashboards, Moose APIs, ClickHouse Connect