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🔍 What is Elasticsearch?

Elasticsearch is a search and analytics engine used to store, search, and analyze massive volumes of data quickly.

At Healthcare Manufaktur, we use Elasticsearch to power data-driven applications that need fast access to structured and unstructured data — such as employee records, system logs, healthcare data, or analytics dashboards.

🧱 Core Concepts​

Understanding Elasticsearch starts with 3 main terms:

📦 Index​

An index is like a database in traditional systems. It contains documents with a specific structure.

You can have many indices, for example:

  • hcm-employees
  • logs-2025-04
  • projects-data

📄 Document​

A document is a JSON object that contains your data.

Example:

{
  "name": "Mohamed HANNANI",
  "position": "Data Scientist",
  "location": {
    "lat": 48.7758,
    "lon": 9.1829
  }
}

🏷️ Field​

A field is a key-value pair inside the document. For example:

  • "name": "Mohamed HANNANI"
  • "location": { "lat": ..., "lon": ... }
  • "timestamp": "2025-04-01T08:00:00Z"

Fields can have different types like text, keyword, geo_point, or date.

📚 How We Use Elasticsearch at HCM​

Here’s how Elasticsearch fits into our workflow:

Use CaseExample
🧑 Employee IndexingSearch, filter, and map team members
📈 AnalyticsLog patterns, user activity, system trends
🌍 Geo DashboardsMap employees or facilities by location
🔎 Fast Search ExperienceAutocomplete search bar or filtered lists

Kibana is our main tool to interact with Elasticsearch.

⚙️ Where Does My Data Go?​

Every time you submit data (via Kibana Dev Tools, code, or API), it is stored in:

  1. An index
  2. As a document
  3. Made up of fields

This structure helps us query it fast and visualize it in Kibana.

✅ Up Next​

In the next guide, we’ll learn how to create a new index from scratch using Dev Tools in Kibana.

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