Databricks-DE-Pro Data Sharing and Federation Practice Question
A Data Engineer is using Lakehouse Federation to query a Snowflake database from Databricks. The engineer has created a connection and a foreign catalog. Which statement correctly describes how data is accessed when a user queries a table in the foreign catalog?
⚠ Common exam trap
The trap here is assuming that federation copies or caches data in Databricks, when it actually pushes down queries to the external system.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The query is executed on Snowflake, and only the results are returned to Databricks.
Lakehouse Federation enables querying external databases without moving data. When a user queries a foreign catalog table, Databricks pushes the query down to the external database, such as Snowflake. The external database executes the query and returns only the results. This approach minimizes data transfer and leverages the external system's compute. The foreign catalog provides a seamless experience, but the data remains in the source system.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The data is cached in the Databricks workspace after the first query.
Why it's wrong here
Lakehouse Federation does not cache data in the Databricks workspace. Each query is executed against the external database. While some caching may occur at the database level, Databricks does not persist the data. This ensures that queries always reflect the current state of the external data.
- ✗
The data is copied into Delta Lake before the query runs.
Why it's wrong here
Lakehouse Federation does not copy data into Delta Lake. It queries the external database directly. The foreign catalog acts as a pointer to the external database, and queries are pushed down to Snowflake. Copying data would introduce latency and storage costs, which defeats the purpose of federation.
- ✗
The query is executed on Databricks, and the data is streamed from Snowflake.
Why it's wrong here
In Lakehouse Federation, the query is not executed on Databricks compute. Instead, it is pushed down to the external database. Databricks acts as the query coordinator, but the heavy lifting is done by Snowflake. Streaming data would be inefficient for large datasets and is not how federation works.
- ✓
The query is executed on Snowflake, and only the results are returned to Databricks.
Why this is correct
Lakehouse Federation pushes down queries to the external database when possible. For Snowflake, the query is executed on Snowflake, and only the result set is returned to Databricks. This minimizes data movement and leverages Snowflake's compute. The foreign catalog provides a unified interface, but the execution happens remotely.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Pro practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DE-Pro exam.