DirectQuery vs Import Mode
- nitin rungta
- 18 hours ago
- 2 min read
Introduction
When connecting Power BI to a data source like Snowflake, SQL Server, or Azure, you’re often given two choices:
DirectQuery or Import Mode.
Both have their use cases, strengths, and trade-offs. This blog will walk through their differences using real-world examples — and lightly touch on how cost can also become a deciding factor.
What’s the Difference?
DirectQuery
Power BI connects live to the data source. Every filter, slicer, or visual click sends a real-time SQL query to the source system.
Data is always up to date
But performance depends heavily on the database
Some Power BI features are limited
Can cause significant compute usage on the source
Import Mode
Power BI loads the data once (manually or on a schedule) and stores it in memory.
Data is fast and local
Full Power BI functionality is available
But data is only as fresh as the last refresh
Great for dashboards that don’t need minute-by-minute updates
Common Connectors Supporting Both Modes
Snowflake
SQL Server / Azure SQL
PostgreSQL
Oracle
Databricks
Google BigQuery
SAP HANA
Some sources also support a hybrid approach using composite models.
Case Study 1: Daily Sales Dashboard (Retail Brand)
Scenario:
A retail company needs a daily report of regional sales, product performance, and returns.
Implementation:
Power BI is set to Import mode
Data refreshes every morning at 7 AM
Users view the dashboard throughout the day without issues
Why Import works:
Data doesn't change much during the day
Report loads instantly
No load on the data source after the refresh
Case Study 2: Inventory Monitoring (Logistics Company)
Scenario:
A logistics company needs near real-time tracking of stock levels across 10+ warehouses.
Implementation:
Power BI is connected using DirectQuery to SQL Server
Users monitor dashboards every hour for live stock levels
Warehouses use Medium-tier SQL compute to support performance
Why DirectQuery works:
Data changes rapidly
Users need to act immediately
They’ve accepted slightly slower load times in exchange for real-time data
Case Study 3: Marketing Campaign Dashboard (Cost Tradeoff)
Scenario:
A marketing agency built a client-facing campaign dashboard using DirectQuery on Snowflake.
Problem:
After rollout, their Snowflake bill spiked. Every client click was triggering multiple queries, consuming compute hours even for simple slicers.
Fix:
They switched to Import mode
Added scheduled refreshes every 6 hours
Resulted in 80–90% lower data warehouse costs, with only minor delays in data freshness
Why Cost Matters:
For platforms like Snowflake or BigQuery (where every query costs money), Import mode gives massive cost control while still delivering great performance — especially when data doesn't change second by second.
Conclusion
Use Import mode when:
Data can be a few hours old
You want better performance
You need full Power BI features
You want to control cloud data costs
Use DirectQuery when:
You truly need live data
You are okay with slower performance
Your source system is built to handle the load
If you're unsure which mode is right for you, start with Import — and monitor the refresh pattern. You can always shift to DirectQuery later if real-time needs arise.