Transitioning from Jitterbit Integration to Azure Cloud Architecture for Retail Sales Data Management

This case study provides insights into transitioning from Jitterbit Integration to Azure Cloud Architecture. We look forward to your feedback.

OVERVIEW

As a growing company operating in the retail sector, the need for seamless integration between various retail vendors and the company’s internal systems has become increasingly essential. The business had been relying on Jitterbit to manage these integrations, which included cloud and on-premise agents to handle the complex flow of sales data from multiple sources such as Shopify, Amazon, Faire, and Pottery Barn. However, this approach was not only expensive but also lagged in efficiency, particularly during high-demand periods, such as the holiday season. The decision was made to transition to an Azure-based solution to improve scalability, reduce costs, and enhance the speed at which data is processed and synchronized with the company’s ERP system.

CHALLENGES

The existing system posed several challenges. First, the cost of maintaining Jitterbit’s integration flows—running both in the cloud and on local agents—was becoming prohibitively high, amounting to nearly $200,000 per year. This included not just the cost of the platform itself but also the complexity of maintaining custom-built integration flows for each vendor.

Another significant issue was the system’s speed and scalability. During peak retail seasons, such as from November 15th through January 1st, the company experienced significant delays in processing sales orders. These delays, which often reached up to 1-2 weeks, hindered the company’s ability to respond to market demands and left both customers and internal teams frustrated. Jitterbit’s on-premise agents and cloud systems lacked the flexibility to scale automatically, forcing the company to purchase additional agent licenses and deploy another instance of the system to handle spikes in demand.

SOLUTION

The move to Azure provided a comprehensive solution to these challenges, addressing both the cost and performance issues while offering enhanced scalability and real-time capabilities. Azure’s serverless architecture, particularly using Azure Service Buses and Function Apps, became the backbone of the new system.
The new integration architecture was designed to ingest sales data from retail vendors through multiple channels, like the previous system: API endpoints, FTP CSV files, and direct database queries. However, once the data was ingested, it was transformed into standardized objects that were directly consumable by the company’s ERP system. This transformation process ensured that sales data—whether from Shopify or Amazon—would follow a unified structure, allowing for the seamless creation of key ERP documents such as sales orders, down payments, incoming payments, delivery notes, and invoices.

In addition to managing sales data, the Azure solution also enabled the company to synchronize stock levels with vendors in near real-time. Stock updates could now be triggered automatically based on key events like purchase orders being placed, inventory being received, or orders being fulfilled, canceled, or returned. These stock changes were immediately sent back to the retail platforms, ensuring accurate stock levels were always reflected on sites like Shopify and Amazon, reducing the risk of overselling or stock discrepancies.

The entire process was orchestrated and managed through an orchestrator database, ensuring smooth transitions between tasks and providing control over the flow of data. Error handling was also greatly improved, with real-time monitoring and alerting critical issues, allowing the company to respond immediately when something went wrong.

RESULTS

The transition to Azure resulted in significant cost savings. The company’s annual expenses for the new system dropped to approximately $10,000, a fraction of the $200,000 they had been spending on Jitterbit. Additionally, the new architecture was much more developer-friendly, with coding in C# taking approximately one-third less time to develop compared to the custom flows required by Jitterbit.

In terms of speed, the new Azure-based system outperformed Jitterbit by a wide margin. During the same peak holiday period, where Jitterbit had previously fallen 1-2 weeks behind in processing sales orders, the Azure system was able to keep up with demand, ensuring that no order was delayed by more than a day. This was largely due to Azure’s cloud-native architecture, which allowed for automatic scaling. When demand spiked, Azure’s Function Apps would spin up additional resources on-the-fly and scale down when demand slowed, ensuring the company only paid for the resources it used.

The scalability of the Azure platform also solved one of the most critical issues the company faced with Jitterbit: the need for manual intervention and additional licenses when scaling up. With Azure’s serverless infrastructure, there was no need for additional licenses or instances—scaling happened automatically, as needed.

CONCLUSION

By transitioning from Jitterbit to Azure, the company not only dramatically reduced its costs but also improved the performance, speed, and scalability of its retail data integration processes. The new architecture was able to process sales data and stock updates in near real-time, providing the agility the company needed to stay competitive in a fast-paced retail environment. Azure’s cloud-native approach offered the flexibility and cost-efficiency required to grow the business while ensuring a seamless experience for both internal teams and retail vendors. The success of this transition highlights the power of cloud-native architecture in delivering high-performance, scalable solutions for modern business challenges.