Databricks-DE-Pro Data Sharing and Federation Practice Question
A data engineering team maintains a Unity Catalog metastore in a Databricks workspace. They need to provide an external partner with read-only access to a specific Delta table, but the partner's analytics platform is not Databricks and does not support the Delta Lake protocol. The partner can consume Parquet files over a REST API. Which Unity Catalog feature should the team use to share the table?
⚠ Common exam trap
Watch out — candidates often confuse Delta Sharing with Lakehouse Federation, which is used to query external data sources from Databricks, not to share data outward.
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
✓
Delta Sharing
Delta Sharing is the correct choice because it is the only Unity Catalog feature designed to share Delta tables externally using an open REST protocol. It supports recipients on non-Databricks platforms by serving data as Parquet, which aligns with the partner's capabilities. The other options serve different purposes: Volumes store files, Lakehouse Federation queries external systems, and the SQL Connector is a client library.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Unity Catalog Volumes
Why it's wrong here
Volumes are designed for storing and accessing non-tabular data files within Unity Catalog, not for sharing tabular datasets with external consumers. They do not provide a REST API for Delta Sharing recipients and do not convert Delta tables to Parquet on the fly. Using Volumes would require the partner to mount or access cloud storage directly, which is not the intended secure sharing mechanism.
- ✗
Databricks SQL Connector for Python
Why it's wrong here
The Databricks SQL Connector for Python is a client library that allows applications to connect to Databricks SQL warehouses and run queries. It is not a data sharing mechanism and does not expose data to external partners in Parquet format. The partner would need Databricks credentials and network access, which is not suitable for cross-organization sharing.
- ✓
Delta Sharing
Why this is correct
Delta Sharing is an open protocol that allows sharing Delta tables with external recipients, including non-Databricks clients, via a REST API. It automatically serves the shared data in Parquet format to recipients that do not support Delta, enabling seamless access. This matches the partner's requirement exactly and is the native Unity Catalog sharing feature for this scenario.
- ✗
Lakehouse Federation
Why it's wrong here
Lakehouse Federation enables Databricks users to query external data sources like PostgreSQL or Snowflake without moving data. It is used for inbound federation, not for sharing Databricks data outward to external partners. It would not provide the partner with a REST API or Parquet files; instead, it lets Databricks query foreign systems.
About these practice questions
This Databricks-DE-Pro question is part of Courseiva's 267-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.