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SQL vs Power Query

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Power Query or SQL

Power Query or SQL

This article explains the comparison between the Power Query and SQL. It would focus on various use cases and the features between the two. If you are trying to make sense of which one among the two is worth using, you should give the below comparison a read.

Hope this information helps you make the choice of which tool to use in which use case or context.

SQLPower Query

Learning Curve

Medium. Requires understanding of tables, queries and data.

Requires understanding of Power BI and it's outcome.


Requires database server and data-lake.

Requires external data sources.

User Base

Large developer community, database admin community.

Specific to the Power BI community.

Programming Support

SQL is the query language and also supported by other external languages.

It can be custom coded and extended with M language.

Data Operations

You can perform CREATE, READ, UPDATE and DELETE.

You can perform data transformations on already processed data.

Custom Code

You can custom code stored procedures and routines to automate.

You can write custom code using the power query to perform specific tasks.

Data Source

Database Server

Various data sources (files, services, database) etc.

External Dependency

SQL requires a lot of tools for you for reporting, visualization, query and storage.

Power query is specific to a tool so it is already dependent on single tool.


Every step of the way you would require permission to access the data.

You take permission only when you are working on the data.


Large and requires much understanding of data and database.

Limited to the tool.

Refresh Times

Initial slow, once cached lot easier.

Lot quicker as data is specifically queried by the tool.

Shared Datasets

You can share the data, reports and other queries using tools.

You share what you are using as a data source. You have limited access.

Power Query : Advantages and Disadvantages

Power Query is an engine being used by the Power BI tool. This engine allows the tool to transform the data and also connect the data with the various data sources out there. e.g. MySQL, CSV Files, Snowflake etc.

Power Query allows you to connect with various sources that are out there—for example, files, databases, services, feeds, data lakes, etc. You would be able to connect your desktop and the cloud service with all of those available data sources.

Some of the data sources may require external connectors. These connectors understand what it takes to connect the available data source with the Power BI tool, which makes it easier to process the data further and transform it as required.

Once the data is taken into the tool the further manipulation using the query, transformation and the manipulation becomes easier with power query. You set up a recurring process for accessing the data, transforming it which is a part of the tool and the engine in general.


  • You can't use parameters passing while working with big data.
  • Limited cells that can be previewed.
  • Limited data size processed in buffer (tool limitation).
  • Performance Issues

SQL : Advantages and Disadvantages

SQL is a language that makes it easier for you to design, process and manipulate the data from the database server. You can literally do anything you want with the data and also get much quicker and faster performance of your queries.

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It's lot faster in terms of performance in comparison to the Power Query. It's transformations are lot quicker than the Power Query.

Reporting with SQL can be done per database basis. Each of them have different tools and methods to accomplish the much better report performance. SQL is lot better with it - be it auto reporting and the Machine Learning based reports.

SQL can be used with many other external tools which makes it easy for you to do analysis. There are however lack of the tools from most of the database engines specific to the analysis and the predictive nature of the data. For that you'd find external tools, which makes the use of the Power BI more useful over traditional SQL query.


  • Steep learning curve of SQL Language
  • Simplicity of Single Tool like Power BI for use case.
  • Not suitable for less technically inclined users.
  • Requires external libraries and engines for predictive and prescriptive analysis.

SQL vs PowerQuery - Which is Better?

SQL and Power-query both have their place when it comes to data science and the business intelligence. However SQL requires a lot of work in order to get the result, however the performance and control offered by the SQL is unmatched for the Power BI.

So the power-query is useful only in context where the less technical person wants to analyze the data, numbers and get the reports and the conclusions quickly out there.

In that context, you'd choose which one of the two would be useful for you.

This content is accurate and true to the best of the author’s knowledge and is not meant to substitute for formal and individualized advice from a qualified professional.

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