Replace centralized data warehouses with distributed architecture. Cut cloud costs by 58%, reduce query latency by 94%, and process petabytes at the edge.
1,300 stores | 100M daily events | 3.5 PB data | 58% cost reduction with 16× faster queries
Every GB moved to the center burns money. Scaling vertically makes it worse.
Moving 5 TB/day incurs $13,500/month in egress fees at $0.09/GB. For a 1,300-store retailer, that's just transfer costs-before compute or storage.
Growing from 1,000 to 2,000 stores doesn't double warehouse costs-it triples them. Vertical scaling gets exponentially expensive.
Round-trips to distant data centers slow decisions and frustrate users.
Queries from 1,300 locations travel thousands of miles to central data centers. Store managers wait 3-5 seconds for inventory dashboards.
Store-level analytics lag by hours. By the time central dashboards update, inventory issues or customer trends have already impacted sales.
Regional laws and global operations create legal exposure and operational overhead.
GDPR, CCPA, and regional laws require data to stay local. Centralizing PII and transaction data from international stores creates legal exposure.
Operating 1,300 stores across continents requires duplicate infrastructure and complex replication strategies to meet latency SLAs.
Every query requires expensive network traversal to central location
Data transfer costs grow linearly with business success
Response times degrade as concurrent users and data volume increase
Regional teams wait for centralized resources during peak hours
Built-in, Automated Filtering
Real-Time
Flexible, works with nearly every vendor
Up to 80% Cost Reduction
Built-in, Automated Filtering
Real-Time
Flexible, works with nearly every vendor
Up to 80% Cost Reduction
We'll show you how Expanso helps teams cut warehouse costs 50-70%, improve query response times 10x, and scale horizontally without vendor lock-in.