Orbio Solutions Case Study: Building a Robust Geo-Spatial Data Handling & Query Service
Orbio Solutions developed a fast, scalable geo-spatial data handling and query service using Node.js, MongoDB, and Redis to address performance and scalability challenges.
The Challenge
Business Problem
Orbio Solutions needed a robust geo-spatial query service capable of handling complex queries with speed and accuracy to support their location-based operations.
The Goal
Develop a fast and scalable geo-spatial query service that can handle a large volume of data and user requests without performance degradation.
Technology Stack
Backend
The Solution
Discovery & Architecture
The architecture involved a custom-developed querying service designed with scalability in mind, leveraging read replicas and 2D sphere-based indexing for optimized performance. The custom service allows for thoughtful architectural design where the system distributes load and handles increasing data and query volumes.
Development Phase
The solution involved creating a custom querying service optimized for geospatial data. This included implementing read replicas to reduce load on the primary database and utilizing 2D sphere-based indexing in MongoDB for fast data retrieval. Node.js was used for the backend to handle a large number of concurrent connections.
Key Feature Implementation
Custom Querying Service, Read Replicas, 2D Sphere-Based Indexing, Caching
The Results
Performance
The service achieved fast response times for geospatial queries through the use of read replicas and optimized indexing.
Scalability
The solution is designed to handle increasing data volumes and query loads without performance degradation, ensuring scalability for future growth.
User Impact
Improved user experience due to faster map loading and search results.
Business Efficiency
Enables real-time analytics and supports efficient location-based operations.