Which data manipulation tool allows you to graphically design the answer to your business questions?

SQL, or structured query language, is an integral part of business intelligence because it’s the only way to speak to relational databases. In fact, it’s so important that one of the defining characteristics separating business intelligence tools from each other is how they use SQL.

One way of thinking about it is that SQL allows you to ask questions and get answers about your data, and each BI tool provides a different method for asking those questions and delivering answers. And the answers you do find will then help you make data-driven decisions about your business that can develop into a significant competitive advantage.

We’ve compared different business intelligence tools before, but knowing how each interacts with SQL in order to create data visualizations will help you decide on the right tool for your organization.

If you need a more polished tool that’s ready to go out of the box, a paid data-visualization tool for SQL is a good way to go. Each has a unique way of dealing with SQL and visualizing data, so what’s good for other companies may not be the right choice for you.

1. Power BI

Microsoft’s Power BI is a business intelligence tool that’s integrated into the Microsoft ecosystem alongside Excel, Access, SQL Server, and others.

How Power BI Uses SQL

Power Query Editorallows you to build queries in Power BI. You have the option to use the series of menus and options to build a simple query with little to no code, or you can go to advanced settings and use SQL directly.

A few things to know

• Power BI is powerful, but will always work best with tools in the Microsoft ecosystem. If your technology stack doesn’t revolve around Microsoft products, you may run into small hiccups here and there.
• After gathering your data with SQL, Power BI has a proprietary XML language called Data Analysis Expressions (DAX) that’s used to model and visualize data.
• Power BI isn’t well suited to handling relational databases, which SQL relies on. James Anderson’s TrustRadius review said, “The relational database only allows one true join so you have to get creative.”

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2. Chartio

How Chartio uses SQL

Chartio has a proprietary SQL language called Visual SQL, which sits on top of SQL to make it simpler for everyone to use. It’s essentially a drag-and-drop interface to build queries.

We made it to fit the needs of three types of users:

1. Anyone in the organization, including business end users, who wants to build complex queries with no coding
2. Power users, who can move faster with the ability to switch seamlessly between Visual and raw SQL
3. SQL experts, who can use industry-leading SQL editing features, like version control, autocomplete, and interactive filter tables

A few things to know

• Chartio is built for scaling, which means it can help any company, from the scrappiest of startups to the world’s largest multimedia news provider.
• Visual SQL doesn’t replace SQL, it augments it, so you don’t need to learn a new way of writing SQL or get used to “Chartio’s way” of making queries.
• These queries create dynamic dashboards that are easy to edit, share, and collaborate on with your entire organization.

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3. Looker

Looker is a business intelligence tool with some powerful proprietary technology used to visualize data. It was was recentlyacquired by Google Cloud, putting its future as a stand-alone tool into question.

How Looker uses SQL

Looker uses a proprietary language called LookML to create SQL queries and model data. It made waves when it was first introduced, but it has become almost another language to learn alongside a decent knowledge of SQL.

A few things to know

• LookML can speed up workflow for data analysts, but it’s built for them, not end business users. This can create a bottleneck if LookerML is not used correctly.
• Looker Blocks are a robust library of prebuilt code blocks that help you accomplish a wide variety of data visualizations out of the box.
• Looker has its own way of referring to the process of data visualization, which some find unintuitive. Bill Ulammandakh on Quora said, “Expect to be confused and learn a lot of weird and arbitrary terminology when ramping up with Looker.”

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4. Tableau

How Tableau uses SQL

Tableau has a set of selections and filters to query data, as well as a Custom SQL option to code your queries.

A few things to know

• Tableau is a legacy giant that has powerful visualization features but hasn’t made big strides in usability. Even a Tableau fan said you’re “require[d] to invest 2-4 weeks, and you will gain 80% of the good parts of Tableau.” And Sara D, on her G2 review said, “There is a very steep ramp-up to use [Tableau].”
• Tableau has one of the larger user bases of all business intelligence tools, so there is decent community support around it.
• Because of its name recognition, Tableau can charge quite a bit for its full services. Overall, that means it’s moving up to focusing on larger enterprise organizations and leaving smaller companies behind. One user on Reddit summed it up like this at the end of their post exploring Tableau’s usefulness at the enterprise level: “Is it just me or is licensing crazy expensive?”

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5. Sisense for Cloud Data Teams

How Sisense for Data Teams uses SQL

Sisense for Cloud Data Teams has a fairly standard SQL editor but can streamline querying with shortcuts and saved snippets.

A few things to know

• Sisense for Cloud Data Teams is not a tool for small or growing companies — it’s meant for enterprise-level data analysis.
• Some reviews mention that the dashboards are fairly basic, without additional coding with R and Python. An IT administrator on G2 said, “The actual … dashboards are relatively basic.” Another G2 reviewer echoed this by saying, “Formatting controls are very limited.”
• It’s a part of the larger Sisense ecosystem of business intelligence software, which is great if you’ve bought into it, but it may require some big transitions if not.

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6. Domo

How Domo uses SQL

Queries in Domo are run through their DataFlow function, where you select multiple databases and can choose to transform that data directly with SQL.

A few things to know

• Domo made waves early on in its life but recently has gained a reputation for poor customer support. One Capterra reviewer said, “The support case has been open for nearly a month and has just been escalated to someone that appears to know how to read the code I have been sending them to trouble shoot THEIR integration.” You may find similar sentiments on other review sites and forums.
• That said, Domo does consistently end up at the front of the pack in annual reports, such as G2’s Analytics Platform rankings.
• Also, Domo’s mobile application is one of the first of its kind and can offer powerful BI to employees on the go.

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7. Mode

How Mode Uses SQL

Mode has a SQL editor, but once a query is executed, it can be sent to the Helix Data Engine, where you can create dashboards and model data using HTML, JavaScript, R, and Python.

A few things to know

• Mode’s full data-visualization functionality is only accessible with deep knowledge of coding. HTML and JavaScript can be used for styling dashboards, while R and Python can be used to dive deep into data science. It provides a lot of power if you’re a coding wiz.
• Mode uses Notebooks to combine SQL with R and Python. They get good reviews by data scientists but are not meant for data analysts, let alone the end business user.
• Mode is not a small tool. They’re generally aiming for Fortune 500-level companies.

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8. Klipfolio

Klipfolio is a data-visualization tool that focuses almost exclusively on dashboarding. As we covered in our article on business intelligence tools, some don’t even consider it a full BI tool.

How Klipfolio uses SQL

Klipfolio allows you to use SQL if you enter your query when you configure a SQL-based data source.

A few things to know

• Klips are Klipfolio’s proprietary XML files that function as a library of prebuilt visualizations.
• While Klips can speed up workflow, a common theme in reviews is that there is a learning curve to get used to them. Ross V. on Capterra said, “It’s rather complex to create custom reports.” And on G2, Thomaz F. said, “I feel some of the automation/updating functions could be a bit easier to achieve.”
• Klipfolio is great if you prioritize dashboarding above all else. If your focus is on querying and diving into the data, you may want to look at another solution.

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Open-source data-visualization tools are free and community-driven, which makes them a great option for small companies with technically skilled employees. But it’s not all roses — there are some quirks to work through in order to get the most out of these tools. What you save in money may cost you time and effort.

Pros

• These open-source tools are free, but some have the option for a paid upgrade.
• They’re self-hosted, which gives you complete control because you’re not reliant on another company or service to host your BI tool.
• Open source lets you tap into the brain trust of the community.

Cons

• There is little to no customer support. If you have an issue, you have to figure it out yourself or go spelunking in the community forums.
• They all require technical know-how to get up and running.
• Due to the need for technical knowledge, these tools don’t scale as well as their paid counterparts. If you want a tool to grow with you, it’s up to you to make it scalable.

Here’s the rundown for three of the biggest open-source data-visualization tools.

How Metabase uses SQL

Metabase uses an “Ask a Question” function, which lets you ask a simple question in plain English (or 14 other languages). You can also use SQL to query the data directly if you havethe right permissions to use the SQL editor.

A few things to know

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2. Redash

Redash (sometimes stylized as Re:dash) is an open-source business intelligence tool that started off as a side project and has grown quickly into a big player in the open-source business intelligence scene.

Databricks recently acquired Redash, which will likely shift its focus towards more intense data science tasks. It also introduces uncertainty into the future of investing in Redash as your main data visualization tool as opposed to the other independent tools.

How Redash uses SQL

Redash has a fairly standardquery editor that allows you to use the query language of your data source. So if it’s a relational database, you can use SQL to query the data.

A few things to know

Learn more

• Article on the History of Redash
• Redash Forum
• G2 Reviews of Redash

3. Apache Superset

How Apache Superset uses SQL

Creating dashboards and querying data in Apache Superset is done in its SQL Lab, which integrates well with Apache Druid, an open-source database that uses Apache.

A few things to know

Learn more

It All Depends on How You Use SQL

Each business intelligence tool has its own philosophy for querying data with SQL, and finding which one aligns most with your company’s workflow may take some trial and error. The good news is that each of these tools has a free trial option (or is completely free in the case of the open-source tools), so there’s no excuse not to dive in and try them out.

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