Elasticsearch vs relational databases - Practice Questions

Challenge - 5 Problems

❓ Predict Output

intermediate

Elasticsearch Query Result Count

Given the following Elasticsearch query on an index with 100 documents, 30 of which have the field status set to active, what is the total hits count returned by this query?

Elasticsearch

{
  "query": {
    "term": { "status": "active" }
  }
}

A 70

B 30

C 0

D 100

💡 Hint

The term query matches documents where the field exactly matches the given value.

The term query filters documents with status exactly equal to active. Since 30 documents have this field value, the total hits count is 30.

🧠 Conceptual

intermediate

Data Model Differences

Which statement best describes a key difference between Elasticsearch and relational databases in how they store data?

A Elasticsearch stores data as JSON documents optimized for search, while relational databases store data in tables with fixed schemas.

B Elasticsearch uses tables and rows like relational databases but adds full-text search capabilities.

C Both Elasticsearch and relational databases store data as key-value pairs without schemas.

D Relational databases store data as JSON documents, while Elasticsearch uses fixed schemas with tables.

💡 Hint

Think about how flexible the data format is in each system.

Elasticsearch stores data as flexible JSON documents designed for fast search and analytics. Relational databases use structured tables with fixed columns and schemas.

🔧 Debug

advanced

Why Does This Elasticsearch Query Fail?

Consider this Elasticsearch query that tries to filter documents where age is greater than 30: { "query": { "range": { "age": { "gt": 30 } } } } Which option explains why this query might fail or return no results if age is stored as a text field in Elasticsearch?

A Range queries require numeric fields; if <code>age</code> is text, the query will not work as expected.

B Elasticsearch does not support range queries on any field type.

C The syntax of the range query is incorrect; it should use <code>greater_than</code> instead of <code>gt</code>.

D The query is missing a <code>filter</code> wrapper around the range clause.

💡 Hint

Check the data type requirements for range queries in Elasticsearch.

Range queries only work on numeric, date, or comparable fields. If age is mapped as text, the query will not filter correctly.

❓ Predict Output

advanced

Relational Database Join vs Elasticsearch Nested Query

In a relational database, joining two tables returns combined rows. Which Elasticsearch query type best mimics this behavior for nested objects within documents?

A Range query

B Term query

C Match all query

D Nested query

💡 Hint

Think about how Elasticsearch handles arrays of objects inside documents.

The nested query allows searching within nested objects inside a document, similar to how joins combine related rows in relational databases.

🚀 Application

expert

Choosing Between Elasticsearch and Relational Databases

You need to build a system that supports complex transactions, strong data consistency, and structured reporting. Which database type is generally more suitable for this use case?

A Elasticsearch, because it is optimized for complex transactions.

B Elasticsearch, because it provides fast full-text search and flexible schemas.

C Relational databases, because they support ACID transactions and structured schemas.

D Neither, a NoSQL key-value store is better for transactions.

💡 Hint

Consider which system guarantees strong consistency and transactional support.

Relational databases are designed for ACID compliance, ensuring strong consistency and transactional integrity, which is essential for complex transactions and structured reporting.