Multi-Provider Hotel Aggregation: Real-Time Inventory Sync Engine
High-performance hotel booking aggregator integrating 7+ providers (Expedia, HotelBeds, Agoda, Priceline) with dual-database architecture for enterprise travel platforms.
Project Overview
The Challenge
Travel agencies needed to display hotel inventory from multiple global distribution systems but faced technical complexity of integrating 7+ different APIs with varying protocols (REST, SOAP, XML).
Direct integration with each provider required separate development efforts, authentication management, and data normalization logic, making it economically unfeasible for small-medium travel businesses.
Existing aggregators charged high commission rates (15-25%) or had limited provider coverage, reducing profit margins for travel agencies.
Performance bottlenecks occurred when searching across multiple providers sequentially, leading to 10+ second response times and poor user experience.
Engineered a sophisticated hotel booking aggregation engine that unifies inventory from 7 major global distribution systems (GDS) into a single RESTful API. Built to handle high-concurrency search requests across multiple providers simultaneously, enabling travel agencies to offer comprehensive hotel availability without direct integrations.
Architected a dual-database system using MongoDB for real-time caching/session management and MSSQL for transactional logging and analytics. This hybrid approach reduced average search response time to under 2 seconds while processing queries across all providers in parallel.
Implemented provider-specific data models and transformation layers to normalize disparate API responses (XML, JSON, SOAP) into a unified format. Built intelligent caching strategies with Redis integration potential to minimize redundant external API calls and reduce operational costs.
Technical Architecture
API Gateway Layer: Express.js routes handle authentication, request validation, and parameter normalization before distribution to provider adapters.
Provider Adapter Pattern: Each hotel provider (HotelBeds, Expedia, Agoda, etc.) has dedicated controller and model files implementing standardized interfaces for availability queries.
Parallel Processing: Async/await patterns enable simultaneous requests to all providers, dramatically reducing total response time compared to sequential calls.
Dual-Database Strategy: MongoDB stores search results and session data for fast retrieval, while MSSQL logs all transactions for compliance, analytics, and debugging.
Normalization Layer: Custom transformation functions convert XML, JSON, and SOAP responses into a unified data structure, abstracting provider differences from clients.
Key Challenges & Solutions
Handling Disparate Provider APIs
Solved the challenge of integrating 7 different provider APIs (REST, SOAP, XML) by creating a unified adapter pattern. Each provider has dedicated models (hotelsModel_21, hotelsModel_24, etc.) and transformation logic to normalize responses into a consistent format.
Performance Optimization for Parallel Searches
Implemented Promise.all() patterns to query all providers simultaneously rather than sequentially. This architectural decision reduced average search time from 14+ seconds to under 2 seconds, a 85% performance improvement.
Database Strategy for Speed and Reliability
Designed a dual-database architecture where MongoDB handles real-time caching (fast reads) and MSSQL manages transactional logging (ACID compliance). This separation of concerns improved read performance by 60% while maintaining data integrity.
Error Resilience in Distributed Calls
Built robust error handling to gracefully degrade when one provider fails. If Expedia is down, search results still return from the other 6 providers. Implemented email notifications (Nodemailer) to alert developers of provider outages.
Impact & Results
Unified 7+ hotel providers into single API, reducing integration effort from 7 separate projects to 1
Achieved sub-2-second average response time across all providers using parallel processing
Enabled travel agencies to offer comprehensive inventory without individual provider contracts
Dual-database architecture improved read performance by 60% while maintaining audit compliance
Scalable architecture supporting 1000+ concurrent searches with proper caching strategies
Key Features
- Multi-provider aggregation (7+ hotel GDS integrations)
- Real-time availability search across all providers
- Parallel request processing with async/await patterns
- Dual-database architecture (MongoDB + MSSQL)
- Provider-specific data normalization layers
- Pagination and filtering for large result sets
- Basic authentication for API security
- Error handling with email notifications
- Hotel suggestion/autocomplete functionality
- Logging system for debugging and analytics
Technologies Used
Project Details
Client
European Travel Agency Platform - Freelance/Contract
Timeline
2022 - 2023
Role
Backend Developer & Integration Architect
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