From Oracle Endeca to Elasticsearch: What 10+ Years in Enterprise Search Taught Me About Modern Search Engineering

For most of my career, I worked on large-scale commerce search systems powered by Oracle Endeca. Search wasn’t just a feature. It impacted revenue, conversions, and user experience at scale. Recently, I started building hands-on projects with Elasticsearch. One thing became clear very quickly: The tools have changed. The fundamentals haven’t. What Years in Search Really Teach You Working on enterprise search platforms forces you to think about: Index design for large catalogs Relevance tuning and ranking strategy Faceted navigation Query performance under load Data modeling for search behavior Those principles are not product-specific. They apply just as much to Elasticsearch. What I Built To validate the transition, I implemented a small commerce-style Elasticsearch project that included: Explicit index mappings (separating text and keyword fields) Weighted relevance boosting (title^3 vs description) Bulk indexing to simulate production ingestion Aggregations for faceted navigation In