Import QVD to SQL Server Automatically
Transferring QlikView QVD files to Microsoft SQL Server often requires complex scripts or workarounds - but not with Advanced ETL Processor. This powerful tool lets you import QVD files into SQL Server automatically, without writing any SQL or code.
What Is a QVD File?
A QVD (QlikView Data) file is a proprietary binary format designed by QlikView and Qlik Sense for fast data storage and retrieval. QVDs are not supported natively by SQL Server, which makes a robust ETL tool essential for integration.
What Is SQL Server?
Microsoft SQL Server is a leading relational database platform used across enterprises for transactional processing, business intelligence, and advanced analytics. It supports T-SQL, stored procedures, integration services, and more.
Why Import QVD into SQL Server?
- Run advanced queries on Qlik data using T-SQL
- Join QVD data with operational or reporting databases
- Make QlikView data accessible to Power BI, SSRS, or custom apps
How to Import QVD to SQL Server - Step-by-Step
1. Launch Advanced ETL Processor
Open the Enterprise Edition of Advanced ETL Processor. Navigate to Tools > Connections and ensure you have connections set up for both QVD and SQL Server.
2. Create a New Transformation
Right-click on a transformation group and select New. This will open the visual dataflow designer.
3. Update Reader Properties
- Drag the QVD Reader onto the canvas (if not already placed)
- Double-click to open the Properties dialog
- Select the correct QVD connection
- Choose the QVD file to import
4. Update Writer Properties
- Drag the SQL Server Writer onto the canvas (if not already placed)
- Double-click to open the Properties dialog
- Select the appropriate SQL Server connection
- Select the target database and table
5. Map and Transform Data
Link fields between the QVD Reader and SQL Server Writer using the AutoMap function or manual mapping. Apply any transformations needed - such as type conversion, string formatting, or calculated fields.
6. Run the Import
Click Execute to load data from QVD into SQL Server. Save the transformation to reuse or automate later.
7. Automate and Monitor
- Use the built-in scheduler to automate the process
- Set up triggers based on file drops or events
- Enable logging, notifications, and rollback on failure
Where this import fits
Import QVD to SQL Server is useful when QVD data needs to feed SQL Server, reporting databases, operational systems, migration jobs, or downstream ETL workflows. Use it when the same import needs validation, mapping, transformations, scheduling, and logs instead of another manual load.
Do not automate the import until the source layout, target table, key fields, write mode, and failure behaviour are agreed. Automation repeats rules; it does not rescue unclear ones.
Useful links for this import
Start with the Advanced ETL Processor Enterprise overview, then download the fully functional 30-day trial. The import-data hub lists the other QVD import workflows.
Business usage examples
Qlik reporting archive
Load QVD extracts into SQL Server so reporting teams can query historical Qlik data outside the dashboard layer.
BI migration staging
Move QVD data into SQL Server staging tables before validation, reconciliation, and warehouse loading.
Scheduled analytics feed
Import recurring QVD files into SQL Server with logs and rejected-row handling instead of manual export steps.
Video Tutorial
FAQ
Can Advanced ETL Processor import QVD to SQL Server?
Yes. Advanced ETL Processor can read QVD, map fields, validate data, write to SQL Server, and log the import.
Do I need to write scripts for the import?
No scripting is required for the normal import workflow. You can configure the reader, writer, mapping, validation, and schedule visually.
Can the QVD import run on a schedule?
Yes. The package can run on a schedule, process matching QVD files, archive originals, and write rows to SQL Server with the same validation rules each time.
Can imported data be transformed before loading?
Yes. You can clean values, convert data types, calculate fields, split columns, and apply lookup rules before writing to the target.
Can bad rows be logged or rejected?
Yes. Add validation rules so rejected rows, failed files, row counts, and error details are visible after each run.
What should I check before the first production import?
Check source layout, target table, key fields, data types, date formats, write mode, archive folder, and failure handling.
When should I not automate the import yet?
Do not automate it until the source layout, target table, key fields, and bad-row handling are clear. Automation repeats rules; it does not invent them.
Can I test the import before buying?
Yes. Download the fully functional 30-day trial, build one small import, and test it with a deliberately awkward sample file.
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