Import vs DirectQuery in Power BI: What SQL Users Need to Know

For SQL users moving into Power BI, one of the first decisions that creates confusion is this:
Should I use Import mode or DirectQuery?

On the surface, the choice seems simple:

• Import copies data into Power BI
• DirectQuery leaves data in SQL Server

In practice, this decision has far-reaching implications — for performance, scalability, maintenance, and even how SQL itself must be written. This article explains what SQL users actually need to know about Import and DirectQuery, based on how Power BI behaves in real reporting environments.

Why Import vs DirectQuery Is a SQL Decision Too

Import vs DirectQuery is often presented as a Power BI setting. In reality, it’s also a SQL architecture decision.

The mode you choose determines:

• How often SQL queries run
• How complex those queries can be
• How indexing should be designed
• Where performance bottlenecks appear

Choosing the wrong mode doesn’t usually fail immediately — it fails slowly, as data grows and usage increases.

Import Mode: What SQL Users Should Understand

In Import mode, Power BI:

• Extracts data from SQL
• Stores it in memory
• Queries the in-memory model, not the database

What This Means for SQL
 

• SQL queries run mainly during refresh
• Performance issues surface during refresh windows
• Query efficiency still matters — but interaction speed is independent of SQL

SQL is typically used to:

• Reduce data volume
• Prepare clean, analytical tables
• Apply stable business logic

Once data is imported, SQL Server is no longer involved in user interactions.

Common SQL Mistakes in Import Mode
 

• Pulling far more data than needed
• Ignoring refresh performance
• Assuming SQL optimisation no longer matters

Import mode rewards good data preparation more than aggressive query tuning.

DirectQuery: What SQL Users Must Be Careful About

DirectQuery behaves very differently.

In DirectQuery mode:

• Data stays in SQL Server
• Every report interaction triggers SQL queries
• SQL performance directly affects user experience

What This Means for SQL
 

• Queries must be fast every time
• Indexing becomes critical
• Poor SQL design is immediately visible
• Concurrency matters as much as query speed

A query that feels “fast enough” in SSMS can feel slow when executed hundreds of times through report interactions.

The Biggest Misconception About DirectQuery

DirectQuery is often chosen to:
“Avoid refresh delays”
or
“Always see real-time data”

What’s often missed:

• DirectQuery shifts complexity from Power BI to SQL
• It increases load on the database
• It requires SQL to be designed for analytical concurrency

Without strong SQL design, DirectQuery almost always leads to:

• Slow visuals
• Timeouts
• User frustration

DirectQuery is not a shortcut — it’s a commitment.

How SQL Design Needs to Change Between Modes

The same SQL design does not work equally well in both modes.

In Import Mode, SQL Should Focus On:
 

• Reducing row counts
• Removing unused columns
• Creating clean fact and dimension structures
• Supporting efficient refresh

In DirectQuery, SQL Must Support:
 

• Fast filtering
• Efficient joins
• Predictable execution plans
• Concurrent analytical queries

This difference is why teams often struggle when switching modes late in a project.

Hybrid and Composite Models: Added Complexity

Power BI also supports mixed approaches:

• Import + DirectQuery
• Aggregations on top of DirectQuery
• Composite models

While powerful, these introduce:

• More complexity
• More SQL tuning requirements
• More places for performance issues to hide

SQL users should approach these models intentionally, not experimentally.

How to Choose in Practice

There is no universal rule — but patterns emerge.

Import mode works best when:

• Data volume is manageable
• Near real-time data is not required
• Reports are heavily interactive
   

DirectQuery works best when:

• Data must stay in SQL
• Data volume is extremely large
• SQL Server is designed for analytics
   

The right choice often depends more on SQL readiness than Power BI features. This interaction between SQL and Power BI is where many architecture decisions succeed or fail. For readers interested in understanding how this choice affects real reporting environments, this Power BI + SQL approach is explained here: Power BI with SQL

Final Thought

Import vs DirectQuery is not about which option is “better”.

It’s about alignment:

• Alignment between SQL design and report usage
• Alignment between performance expectations and architecture
• Alignment between teams who own SQL and Power BI

SQL users who understand this distinction make better design decisions — and avoid painful rework later.

Learning How SQL Design Aligns with Power BI Modes

For those looking to understand how SQL design choices interact with Import and DirectQuery in real projects, the Power BI + SQL course by ExcelGoodies focuses on practical reporting architectures rather than isolated tool features.

Check the Upcoming batch details
 

Editor’s Note

This article reflects recurring architectural discussions observed across Power BI implementations where Import and DirectQuery decisions directly affected SQL design, performance, and long-term maintainability.

Insights compiled with inputs from the ExcelGoodies Trainers & Power Users Community.
 

MS-SQL