Clarifruit streamlines development and improves application performance with MongoDB Atlas

Clarifruit, a leading agriculture technology company, is revolutionizing the fresh produce industry with cutting-edge computer vision and digitization technologies. Their goal is to streamline the quality control process for fruits and vegetables, helping everyone from farmers and growers to distributors and retailers accurately determine the quality of their produce. With Clarifruit’s iOS and Android apps for quality control inspectors in the field, and a web app for managers, the company provides comprehensive tools for assessing everything from the size and color of grapes to the quality of their stems.

As Clarifruit rapidly scaled, its existing data infrastructure (which was built on Amazon RDS for MySQL) faced increasing limitations. The company needed a more flexible and scalable database solution, particularly one that could support a multi-cloud strategy. By transitioning to MongoDB Atlas—including using the local experience for MongoDB Atlas Search with Docker—Clarifruit not only enhanced its agility and application performance but also created a better experience for its customers.

Luke Thompson, Chief Architect, Clarifruit

Because of the intuitive nature of MongoDB’s document model, it was easy for Clarifruit’s development teams to make the switch from the relational approach they had been accustomed to. They migrated from using EC2 instances and MySQL to a containerized Java application with MongoDB Atlas running on two different clouds. In so doing, the company not only moved to a multi-cloud environment but also modernized and introduced more flexibility into the backend of their application infrastructure

And by moving to MongoDB Atlas, Clarifruit was able to accelerate its pace of innovation. “We can iterate more quickly when we’re introducing new features on MongoDB because we’re not bound to a particular schema,” says Luke Thompson, Chief Architect at Clarifruit. “It’s easier for developers to release new features than it was when we had more rigid schemas. Back then, every time we wanted to make a schema change, we had to go through a process to coordinate between developers and manage the database schema update alongside code updates. This sometimes involved downtime and reduced our service availability.”

Luke Thompson, Chief Architect, Clarifruit

The creation of a local experience for search use cases with the Atlas CLI and Docker enabled Clarifruit to finally make the switch to Atlas Search. Developers at Clarifruit were accustomed to building and testing code on their local laptops. Thompson says, “We do work offline occasionally,” Thompson says. “But more frequently, we want to be able to run experiments and quickly iterate and test our code locally. It’s easier to do that if you don’t have a dependency on a remote database.”

Now Clarifruit’s developers can easily build and test new features with Atlas Search on their local machines and have confidence that they will sufficiently mirror behavior in production. Development and testing are also simpler and easier for developers throughout the full software development lifecycle. Say, for example, the team at Clarifruit is building a new feature and it wants to add an Atlas Search index. With the local experience for Atlas Search on Docker, they can make a local copy of a test data set, try different Atlas Search indexes, and compare the differences without impacting other developers by using shared resources and without incurring any costs. “MongoDB’s release of local search with the Atlas CLI and Docker was really what tipped us into finally adopting Atlas Search,” Thompson said.