Building a Scalable Real Estate Search Platform with React and Hapi Microservices
How we built a multi-tenant property search engine with geolocation filtering for a real estate startup - handling complex user roles and map-based searches
Business Challenge
Traditional real estate platforms struggled with complex multi-tenant requirements. Key issues included:
- Multi-role authentication - agents, buyers, landlords needed different access levels
- Geolocation complexity - precise location-based searches with map integration
- Real-time updates - instant property listing changes across all users
- Mobile performance - majority of users searched on mobile devices
Technical Solution: React + Hapi Microservices
Modern Stack Choice: React for dynamic UI, Hapi.js microservices for API, MongoDB for flexible data storage, AWS Lambda for scalable processing.
Architecture Overview
- Frontend - React with TypeScript, Material-UI, Google Maps integration
- Backend - Hapi.js microservices with dedicated SSO authentication
- Database - MongoDB with geospatial indexing for location queries
- Infrastructure - AWS Lambda workers, SQS queues, S3 for file storage
- Integrations - Salesforce CRM integration via microservices
Key Technical Implementation
Dedicated SSO Microservice: Centralized authentication service built with Hapi.js, handling JWT tokens and multi-role authorization for agents, buyers, and landlords.
MongoDB Geospatial Search: 2dsphere indexes for radius-based property queries, calculating distances and ordering by proximity with sub-second response times.
Salesforce Integration: Dedicated microservices with SQS queues and Lambda workers for syncing leads, contacts, and property data between platforms.
Scalable Queue Architecture: AWS SQS for reliable message processing and Lambda functions for background data synchronization tasks.
Business Results
AWS Infrastructure
Production Setup: Lambda functions for microservices, SQS queues for message processing, MongoDB Atlas for managed database, S3 for property images with CloudFront CDN.
Serverless Architecture: Hapi.js microservices deployed as Lambda functions with API Gateway routing and automatic scaling based on demand.
Key Takeaways
- MongoDB geospatial indexes are powerful - 2dsphere indexes dramatically improved location-based search performance
- Dedicated SSO microservice - centralized authentication simplified multi-tenant user management
- Lambda + SQS architecture - serverless processing with queues provided excellent scalability for Salesforce sync
- Hapi.js for microservices - excellent plugin ecosystem and built-in validation made development faster
Building a real estate or location-based platform? I have deep experience with MongoDB geospatial queries, Hapi.js microservices, SSO architecture, and Salesforce integrations. Let's discuss your project.