Elasticsearch

Elasticsearch is a distributed search and analytics engine designed for fast searching, filtering, and analysis of large volumes of data.

It stores information as JSON-like documents and organizes that data into indexes so applications can perform full-text search, structured queries, aggregations, and real-time analytics.

Elasticsearch is commonly used for website search, log analysis, application monitoring, security analytics, and large-scale data exploration.

Also known as: Distributed search engine, full-text search engine, analytics engine.

How Does Elasticsearch Work?

Elasticsearch organizes data into documents and indexes.

A typical workflow includes:

1. Send structured or semi-structured data to Elasticsearch.
2. Store each record as a document.
3. Add documents to an index.
4. Analyze and tokenize searchable text.
5. Build internal search structures.
6. Run queries, filters, and aggregations.
7. Return ranked or aggregated results.

Because the system is distributed, indexes can be divided across multiple servers to improve scalability and availability.

Documents and Indexes

A document is a single record stored in Elasticsearch.

For example:

{
  "product_id": 1001,
  "name": "Wireless Mouse",
  "category": "Accessories",
  "price": 29.99
}

An index is a collection of related documents.

For example, an e-commerce platform may maintain separate indexes for:

products
customers
orders
logs

Indexes allow Elasticsearch to organize and search large datasets efficiently.