Why Boolean and binary types in Elasticsearch? - Purpose & Use Cases

The Big Idea

Discover how simple true/false and raw data types can supercharge your search and storage!

The Scenario

Imagine you have a huge list of items and you want to mark each as either true or false, or store small pieces of data like images or files. Doing this by hand means writing long, complicated code to handle each case separately.

The Problem

Manually managing true/false values or binary data is slow and error-prone. You might mix up data formats, waste space, or make your searches very slow because the system doesn't understand your data type well.

The Solution

Boolean and binary types in Elasticsearch let you store true/false values and raw binary data efficiently. Elasticsearch knows exactly how to handle these types, making your searches faster and your data storage simpler.

Before vs After

✗ Before

PUT my_index/_doc/1
{
  "active": "true"
}

✓ After

PUT my_index/_doc/1
{
  "active": true
}

What It Enables

It enables lightning-fast filtering and accurate storage of true/false flags and binary data, making your search and data handling smarter and more efficient.

Real Life Example

For example, an online store can quickly filter products that are in stock (true) or out of stock (false), or store product images as binary data directly in Elasticsearch.

Key Takeaways

Boolean and binary types simplify storing true/false and raw data.

They improve search speed and reduce errors.

They make your data handling smarter and more efficient.