Leading Online Ordering and Delivery Platform Case Study

Cookie Notice

This site uses cookies for performance, analytics, personalization and advertising purposes.

For more information about how we use cookies please see our Cookie Policy.

Manage Consent Preferences

Essential/Strictly Necessary Cookies

Required

These cookies are essential in order to enable you to move around the website and use its features, such as accessing secure areas of the website.

Analytical/ Performance Cookies

These are analytics cookies that allow us to collect information about how visitors use a website, for instance which pages visitors go to most often, and if they get error messages from web pages. This helps us to improve the way the website works and allows us to test different ideas on the site.

Functional/ Preference Cookies

These cookies allow our website to properly function and in particular will allow you to use its more personal features.

Targeting/ Advertising Cookies

These cookies are used by third parties to build a profile of your interests and show you relevant adverts on other sites. You should check the relevant third party website for more information and how to opt out, as described below.

100%

of data in Amazon S3

10,000

daily inquiries

250 TB

data processed daily

Region

Americas

Industry

Transportation & Logistics

Environment

AWS

Solution

Enterprise

Employees

1000+

We primarily use Starburst for reporting and dashboard queries, but the platform supports a variety of use cases, including ad-hoc queries, complex queries, and some exploratory, machine learning, and data science activity. We’ve even started using it to serve A/B testing experiment results and for real-time reporting and visualization.

Anonymous

Data Engineering Manager

100%

of data in Amazon S3

10,000

daily inquiries

250 TB

data processed daily

About

The country’s leading online and mobile food ordering and delivery marketplace operates in over 2,200 U.S. cities and London. The company processes 521,000 daily orders and serves 19.3 million active diners.

This activity drives tremendous data growth. To remain the leader in an increasingly competitive market, especially after the pandemic-fueled uptick in mobile ordering, the company needed to make its data available immediately for internal analysis.

Challenge

Not long ago, the company had a major data center footprint and relied on an expensive Java and MySQL stack. The company streamed data into an AWS data lake, but open source Trino on Amazon EMR failed to deliver the necessary performance and efficiency. Unsuccessful queries that occurred when using EMR were driving up costs.

As the business rapidly grew, the company recognized that this approach would not scale cost-effectively. It needed enterprise-grade software and a more available, scalable, and flexible system.

Solution

The data engineering team selected Starburst Enterprise as the query engine to help users transform raw data into actionable business intelligence. The company operates a cloud-only environment with 100% of its data in its Amazon Simple Storage Service (S3) data lake, and uses Starburst for reporting and dashboard queries, with 90 to 95% of analytics coming from Starburst.

Along with two production clusters in AWS, the data engineering team uses on-demand Starburst Enterprise clusters for job-specific workloads throughout the day. This allows the team to dynamically spin up a cluster, run queries, and then power it down again to minimize compute costs.

Results

Deploying Starburst Enterprise resulted in these direct benefits to the company.

Faster performance and a higher successful query rate, leading to additional adoption by end users.
Reduced customer cost due to fewer unsuccessful queries.
Cluster optimization is based on use cases, allowing each cluster to perform better.
Improved security and stronger controls around data access that is essential for publicly traded companies.

As the company works to secure its leadership in an increasingly competitive market, Starburst Enterprise provides the data engineering team with the reliable, scalable, high-performing, cost-effective platform it needs to support end users and extract business intelligence.