Case Study: IEEE GlobalSpec achieves 2x faster, more relevant product search with Elastic

Replacing Legacy Product Search with Elasticsearch at IEEE GlobalSpec

IEEE GlobalSpec is a global engineering community (nearly 9 million registered professionals) that connects manufacturers, distributors and service providers with engineers through trusted technical content and tools. Facing a legacy, home-grown Java/Lucene search stack—plus disparate search layers (in-memory Lucene, SQL full-text, Solr)—the company needed a simpler, faster, and scalable search architecture and an opportunity to rewrite search from the ground up.

IEEE GlobalSpec migrated to the Elastic Stack (Elasticsearch, Logstash, Kibana) behind an Artemis Search Gateway, using A/B testing and parallel data builds to flip traffic safely. They implemented features like diversified_sampler + top_hits for product-breadth, interpretation-ranking for ambiguous queries, and dfs_query_then_fetch to normalize IDF across uneven index sizes. The result: search performance doubled, user engagement and key metrics improved, developers became more productive, and the unified Elastic backend reduced costs while improving logging, debugging and analytics.

IEEE GlobalSpec

Kathleen DeRusso

Principal Software Engineer