Case Study: Qualtrics achieves real-time, scalable analysis of open-text survey responses with Crate.io's CrateDB

Using Cratedb to Augment Analysis of Free-Form Text with Machine Learning Algorithms

Qualtrics, a leader in experience management software, needed to analyze massive volumes of open-text survey responses in its Text iQ offering—thousands of free-form comments per hour—so it could apply machine-learning models to cleanse, categorize and score sentiment in real time. To meet this challenge Qualtrics chose Crate.io’s CrateDB as the database backbone for processing and querying full-text data at scale.

Crate.io implemented CrateDB, a distributed, cloud-native SQL database that delivers real-time full-text querying, easy containerized scaling and fault tolerance. As a result, Qualtrics can run ML-driven categorization and sentiment analysis on thousands of feedback items per hour, achieve high availability with self-healing after VM failures, and deliver faster, scalable insights to its customers.

Qualtrics

Jeffrey Starr

Software Engineer