Commercial Real Estate GIS scaling through Cloud Migration and Application Modernization
Achieving 20x Faster Map Creation and Reduced Costs for Commercial Real Estate GIS
Managing vast datasets and creating accurate maps were ongoing challenges for a commercial real estate client. Their legacy GIS application, built on outdated PHP and hosted on-premises, struggled with performance, stability, and scalability—resulting in slow map creation and inefficient retailer management.
Challenges
Slow, Unreliable, and Costly Map Creation
- Retailer Logo Bottlenecks: The system frequently failed to fetch and render retailer logos efficiently on the maps.
On-Premises Storage Issues: Storing logos locally consumed substantial memory, causing frequent crashes and high server loads.
Inefficient Geospatial Queries: Relational database structures slowed down spatial queries, making map creation sluggish and unreliable.
Retailer List Management: Manual updates to retailer data took days due to the absence of an automated pipeline.
The Solution
Scalable Cloud Migration and Modernization
We addressed the challenges through a comprehensive application overhaul:
Cloud Migration & Modern Tech Stack: Rebuilt the application using React, Express.js, and MySQL, and hosted it on AWS ECS for auto-scaling and improved stability.
Optimized Retailer Logo Management: Moved logo storage to AWS S3 and served assets via CloudFront, reducing memory usage and boosting performance.
High-Performance Geospatial Search: Replaced relational geospatial queries with AWS OpenSearch, dramatically accelerating spatial data retrieval.
Automated Retailer Data Pipeline: Implemented AWS Glue to automate retailer list and logo updates, replacing time-consuming manual processes.
Cost-Effective Map Rendering: Switched from Google Maps to Mapbox, meeting functional requirements while significantly reducing expenses.
The Impact
Speed, Efficiency, and Cost Savings
- 20x Faster Map Creation: Geospatial queries now run dramatically faster, boosting productivity.
- 50% Cost Reduction: Switching to Mapbox significantly lowered mapping expenses.
- Streamlined Retailer Management: Automation reduced update times from days to minutes.
- Enhanced Scalability and Stability: Cloud-based architecture eliminated server crashes and improved overall performance.
Technologies Used:
- React
- Express.js
- MySQL
- OpenSearch
- AWS
- Mapbox