Elasticsearch - Search Engine
What is Elasticsearch?
Elasticsearch is a distributed real-time search and analytics engine based on Apache Lucene. Created in 2010 by Shay Banon, it offers advanced search capabilities, data analysis, and aggregations at scale.
Benefits of Elasticsearch - why it dominates search and analytics?
Main advantages of Elasticsearch - real-time search, horizontal scaling, ELK Stack, analytics on petabytes of data
Challenges of Elasticsearch - honest assessment
Elasticsearch limitations - memory consumption, configuration complexity, eventual consistency, enterprise costs
What is Elasticsearch used for?
Main Elasticsearch applications in 2025 - log analytics, site search, monitoring, business intelligence
Log analytics and system monitoring
Application log centralization, performance monitoring, security analytics, real-time observability
Netflix (monitoring 1000+ microservices), Uber (ride pattern analysis), Airbnb (booking system monitoring)
Website and application search
Advanced product search, content discovery, document search with autocomplete, filters, faceted search
GitHub code search, Stack Overflow question search, Medium article discovery, e-commerce product search
Application and infrastructure monitoring
APM (Application Performance Monitoring), infrastructure monitoring, alerting, SLA tracking
Slack system monitoring, Discord performance tracking, GitLab infrastructure observability
Business Intelligence and analytics
Real-time dashboards, KPI monitoring, business metrics, operational intelligence, customer analytics
Tinder user behavior analytics, LinkedIn job matching insights, Shopify merchant analytics
FAQ: Elasticsearch – Frequently Asked Questions
Complete answers about Elasticsearch – from basics to production clusters and performance optimization