A Retail Giant’s Journey From Traditional to Transformational

One the largest and oldest department store chains in the world, Macy’s embraces its storied history but like any business needs to be able to adapt to new times and new customer demands. 

Facing a heavy increase in traffic for its ecommerce site and omnichannel catalog, Macy’s needed something far more powerful and flexible than the relational database it was using.

Macy's
Macys Logo

One of the things I don't worry about at night anymore is a 10x growth in the catalog. We can easily handle that. It's just not a problem technically or for the business. If they want to grow the catalog, we can do it. And we can do it fairly inexpensively. I don't think that's necessarily the case with proprietary relational technologies.

Peter Connolly

Senior Architect, Macy's

The Opportunity

Macy’s wanted to improve its omnichannel customer experience with real-time updates on store and inventory data, and by integrating website, mobile, store, and partner applications.

Macy’s was also growing rapidly, and the rapid expansion of its ecommerce business was putting tremendous stress on its data technology. It found itself suddenly needing to handle 10 times the amount of products and UPCs.

Macy’s heavily normalized relational databases simply could not handle the uptick in growth. Essentially—the size and complexity of Macy’s data grid was starting to cause failures, and solutions such as adding an in-memory data grid were becoming extremely expensive.

The Solution

The Results

>6x

Reduction in catalog data refresh time (from three hours to less than half an hour)

>50%

Growth in sales of Macy’s app in first half of 2018

>30%

Increase in stock price so far in 2018