Rakuten Accelerates Query Performance and Modernizes Analytics Program with AtScale
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- AtScale
- Snowflake
- Tableau
- Amazon Web Services (AWS)
Tech Stack
- Hadoop
- SQL
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Analytics & Modeling - Big Data Analytics
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- E-Commerce
- Retail
Applicable Functions
- Business Operation
- Discrete Manufacturing
Use Cases
- Inventory Management
- Predictive Maintenance
- Supply Chain Visibility
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
Rakuten is a shopping rewards company that leverages data on shopper behavior, pricing, and commissions to create compelling offers for their customers, who receive cash-back incentives from Rakuten. With over 13 million e-commerce customers and partnerships with 70+ businesses, Rakuten depends on sophisticated analytics and data management to maintain a differentiated offering in the highly competitive e-commerce industry. While Rakuten originally consolidated data from multiple siloed systems to a single, on-premises data lake built on Hadoop in 2016, they still faced challenges related to maintaining the environment. The sheer electrical costs of hosting their own internal server farm as well as the expensive hardware required presented obstacles for this fast-growing operation.
The Challenge
Rakuten, a shopping rewards company, had moved from their initial SQL database in 2014 to an AtScale-powered Hadoop solution in 2018. However, this wasn’t sufficient and they soon began to experience a resource crunch based on the sheer size of their database. Rakuten's existing architecture meant that business users didn't have the computing resources necessary to work with large datasets. This led to competition between business units for hard disk access, memory, and CPU time. The internal team was frustrated with the competition for resources, and the operational overhead and associated hardware and electricity costs also meant the solution was no longer cost-efficient. That, coupled with the continuous processing demands on storage infrastructure, forced Rakuten to consider new solutions for their data needs. They knew they needed more processing capability and flexibility to continue serving their customers effectively.
The Solution
AtScale helped Rakuten transition their analytics to the cloud while still retaining all the analytical capabilities they had built, enabling them to deliver consistency for their team. AtScale insulated their Tableau-based reports and dashboards from changes in underlying raw data. While location and schemas changed, the AtScale model was untouched, allowing them to preserve their investment. Once they had moved their data to Snowflake, AtScale was able to help Rakuten better optimize their costs by right-sizing cloud resource consumption based on real-time usage. AtScale also helped smooth out and mitigate user concurrency challenges without requiring additional compute resources and leveraged intelligent aggregates to accelerate query performance while keeping cloud costs down.
Operational Impact
Quantitative Benefit
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