What is Elastic Search?
Elasticsearch is a distributed, RESTful search and analytics engine designed for fast full-text search and real-time data analysis. It's built on Apache Lucene and is commonly used for log analytics, search functionality, and data exploration at scale.
🔍 In Simple Terms:
Elasticsearch helps you store, search, and analyze huge volumes of data quickly and in near real-time. It's like Google for your app’s data.
🔧 Core Features:
| Feature | Description |
|---|---|
| Full-Text Search | Quickly searches text with advanced capabilities (like stemming, synonyms, relevance ranking). |
| Real-Time Indexing | New data is searchable almost immediately after ingestion. |
| Scalability | Built to scale horizontally across nodes; supports sharding and replication. |
| REST API | All operations (search, index, update, delete) are done using simple HTTP requests. |
| JSON-Based | Data is indexed and queried in JSON format. |
| Distributed by Default | Works on clusters; handles failover, replication, and load balancing. |
🧱 Common Use Cases:
- Application and website search boxes (e.g., e-commerce search)
- Log analytics (when used with Logstash & Kibana — the ELK Stack)
- Monitoring and observability (metrics, traces, logs)
- Autocomplete, Suggestions, and Faceted search
- Business Intelligence dashboards
🔗 Elasticsearch in the ELK Stack:
- E = Elasticsearch (search engine)
- L = Logstash (data ingestion & transformation)
- K = Kibana (data visualization UI)
Together, they form a powerful solution for log analysis and real-time monitoring.
🛠️ Example Use in Java:
You can use Elasticsearch clients like:
Then index a document: