Elasticsearch vs relational databases - Hands-On Comparison

Comparing Elasticsearch and Relational Databases

📖 Scenario: You work in a company that stores customer data. You want to see how Elasticsearch and relational databases handle searching and storing data differently.

🎯 Goal: Build a simple example to store and search customer data using Elasticsearch queries and compare it with relational database style queries.

📋 What You'll Learn

Create a sample dataset of customers with name and age

Set a minimum age filter value

Write an Elasticsearch query to find customers older than the minimum age

Print the query JSON to see the output

💡 Why This Matters

🌍 Real World

Elasticsearch is used for fast, flexible searching in big data, while relational databases are used for structured data storage and complex transactions.

💼 Career

Understanding both helps in roles like data engineering, backend development, and search engine optimization.

1

Create the customer data

Create a variable called customers that holds a list of dictionaries with these exact entries: {"name": "Alice", "age": 30}, {"name": "Bob", "age": 25}, and {"name": "Charlie", "age": 35}.

Elasticsearch

# Create the customers list with exact entries
# Your code here

Need a hint?

Use a list with dictionaries for each customer.

2

Set the minimum age filter

Create a variable called min_age and set it to 30.

Elasticsearch

customers = [
    {"name": "Alice", "age": 30},
    {"name": "Bob", "age": 25},
    {"name": "Charlie", "age": 35}
]
# Set the minimum age filter
# Your code here

Need a hint?

Just assign the number 30 to min_age.

3

Write the Elasticsearch query

Create a variable called es_query that holds a dictionary representing an Elasticsearch query to find customers with age greater than or equal to min_age. Use the range query on the age field with gte set to min_age.

Elasticsearch

customers = [
    {"name": "Alice", "age": 30},
    {"name": "Bob", "age": 25},
    {"name": "Charlie", "age": 35}
]
min_age = 30
# Create the Elasticsearch query dictionary
# Your code here

Need a hint?

Use nested dictionaries to build the query structure.

4

Print the Elasticsearch query

Write a print statement to display the es_query variable.

Elasticsearch

customers = [
    {"name": "Alice", "age": 30},
    {"name": "Bob", "age": 25},
    {"name": "Charlie", "age": 35}
]
min_age = 30
es_query = {
    "query": {
        "range": {
            "age": {
                "gte": min_age
            }
        }
    }
}
# Print the Elasticsearch query
# Your code here

Need a hint?

Use print(es_query) to show the query.