If by “ES” you mean Elasticsearch (the super-popular tool used for searching through massive amounts of data), you’ve come to the right place. It can feel a bit intimidating at first because it uses its own vocabulary, but once you get the core concepts down, it’s incredibly powerful.

Think of Elasticsearch like a massive, lightning-fast digital filing cabinet. Here is how to get started as a beginner.

---

1. Learn the Core Vocabulary

Before you write any code, you need to know how Elasticsearch talks about data compared to a traditional SQL database:

SQL Database	Elasticsearch	What it means in plain English
Table	Index	A place where you store a collection of similar things (like a “products” index).
Row	Document	A single item or record, written in JSON format.
Column	Field	A specific piece of data inside that item (like “price” or “product_name”).

---

2. The Big Mental Shift: Everything is an API

Unlike traditional databases where you write SQL queries (SELECT * FROM...), you talk to Elasticsearch using HTTP requests (GET, POST, PUT, DELETE). You are essentially sending and receiving JSON data over the web.

Here is how the four basic actions (CRUD) look in Elasticsearch:

Create (Put data in)

To add a document to an index called recipes, you send a POST request:

POST /recipes/_doc/1
{
  "title": "Perfect Chocolate Chip Cookies",
  "baking_time_minutes": 12,
  "ingredients": ["flour", "sugar", "chocolate chips"]
}

Read (Get data out)

To grab that exact recipe by its ID, you send a simple GET request:

GET /recipes/_doc/1

Update (Change data)

If you want to change the baking time, you send a POST request to the update endpoint:

POST /recipes/_update/1
{
  "doc": {
    "baking_time_minutes": 10
  }
}

Delete (Remove data)

To get rid of it entirely, use the DELETE verb:

DELETE /recipes/_doc/1

---

3. How to Actually Run Your First Search

The real magic of ES is its search capability. It doesn’t just look for exact matches; it understands relevance. To search, you use the _search endpoint and pass a query.

For example, to find any recipe that mentions “chocolate”:

GET /recipes/_search
{
  "query": {
    "match": {
      "title": "chocolate"
    }
  }
}

Elasticsearch will look through your titles, find matches, and score them based on how relevant they are (so a recipe called “Triple Chocolate Cake” will score higher than “Cookies with a hint of chocolate”).

---

4. The Best Way to Practice

Don’t try to run all of this via raw terminal commands (cURL) when you are starting out.

1. Download Docker and spin up a local Elasticsearch container, or sign up for a free trial on Elastic Cloud.
2. Use Kibana (the visual dashboard that comes with ES). Inside Kibana, there is a tool called Dev Tools. It gives you a clean console where you can type the JSON requests shown above, auto-completes your code, and shows you the results side-by-side.