Case Study: Traackr achieves faster, more accurate influencer lists with MongoDB

Traackr - Customer Case Study

Traackr provides brand marketers and PR teams an automated platform to identify and rank influencers by mining blogs, articles and social posts—processing roughly 500k–1M posts per day. Their original HBase-based setup constrained their data model and lacked indexing and ad-hoc query capabilities, preventing the firm from creating strong, accurate relationships among influencers, channels and posts and leading to inconsistent influencer rankings.

Traackr migrated to MongoDB for its flexibility, secondary/compound indexes, ad-hoc queries and easier operations. The new model enabled atypical connections (e.g., linking a blogger to a publisher site), replaced some MapReduce jobs with faster direct computations, improved availability, and sped development—resulting in higher-quality, more reliable influencer lists, better performance and a more attractive platform for developers.

Traackr

David Chancogne

Co-founder and CTO, Traackr