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.
Oct 14, 2018 Superset主要因為使用者體驗不是很好，還有大部分圖表是需要時間維度，但公司如果是要看產品相關的報表，很可能是以旅遊地區、供應商、價格為.
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.
Flood runner 2gamerate. 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.
8 Paid Data-Visualization Tools for SQL
- Seamlessly sync all your business data to Redash and Metabase using Panoply’s built-in ETL. Set up a pipeline in minutes with our simple point-and-click interface, then we’ll handle the ongoing maintenance so you can focus on building reports, not fixing leaky plumbing.
- Redash 的代码结构也很干净，可以排第二，Superset 稍略一筹排在末位。这个结果与定量分析的结论是基本一致。 小结. 本文以 Superset，Redash，Metabase 三个项目的比较为例，介绍了开源项目选择上的一些原则。.
- A Single Source of Truth for Metabase and Apache Superset Power consistent reporting and analysis with Panoply. Sync and store data from over 30+ sources. Keep all your business units happy by connecting their favorite BI tools.
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
Chartio (that’s us! 👋) is a business intelligence tool that empowers everyone to understand and act on their company’s data.
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:
- Anyone in the organization, including business end users, who wants to build complex queries with no coding
- Power users, who can move faster with the ability to switch seamlessly between Visual and raw SQL
- SQL experts, who can use industry-leading SQL editing features, like version control, autocomplete, and interactive filter tables
A few things to know Health promoting schoolshealthy active living.
- 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
Tableau is a giant of the business intelligence world, with legacy visualization features for SQL. It was a trailblazer, but most other tools have caught up since Salesforce acquired this tool.
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.
Source: https://help.tableau.com/current/pro/desktop/en-us/customsql.htm
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
Previously known as Periscope Data, Sisense for Cloud Data Teams is an enterprise-level business intelligence tool designed for efficient data analysis.
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
Domo is a business intelligence tool founded with a mobile-first philosophy that made a splash early on in its life.
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
Mode is a business intelligence tool with a focus on data science that’s designed for large enterprise companies.
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.
Source: https://support.klipfolio.com/hc/en-us/articles/215547018-How-do-I-create-an-SQL-database-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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3 Free, Open Source Data Visualization Tools for SQL
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.
Robot unicorn attackbacon games. 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.
1. Metabase
Metabase is a free open source data visualization tool with a focus on ease of use for nontechnical users. You may see Metabase and Redash (below) referred to around the internet as the two giants of open-source business intelligence.
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
- The “Ask a Question” function may help nontechnical users, but it can turn into another layer to work through. Peter Weinberg of Panoply described it as “tricky to learn the SQL-but-not-quite style data interface.” One user on Reddit said they liked Metabase but used a separate SQL editor to write their queries.
- Metabase Discourse is the community source for getting customer support.
- There is an enterprise version that costs $10,000 a year.
Learn more
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
- Outside of self-hosting, which is free, Redash has three pricing plans based on numbers of users.
- One Reddit user who compared Metabase, Redash, and Apache Superset said that they “found [Redash’s] SQL editor less nice to use.”
- Redash generally doesn’t scale well for larger companies because it limits simultaneous queries to 50. This, combined with many reviews that mention it can be slow, makes it a not-so-ideal choice for companies growing quickly. One G2 reviewer summed it up as, “Sometimes getting simple things can give you a headache.”
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3. Apache Superset
Apache Superset is a free, open source data visualization tool run on Apache, the biggest name in open-source web-server software.
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
Metabase Vs Redash Vs Superset
- Around 62 million websites use Apache. This massive footprint gives the Apache name an open-source pedigree.
- Apache Superset is still in incubation, which means it has not been fully vetted by The Apache Software Foundation (ASF). This can mean a lot of things, but it’s safe to assume it’s not as stable as Redash and Metabase, and it may lack a few features.
- Some users find that Apache Superset is not friendly for nontechnical users. Reddit user u/gordonisadog on the r/datascience subreddit said, “We ran Superset for a while but switched to Metabase. The non-techie users are much happier.”
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Redash Vs Metabase
It All Depends on How You Use SQL
Metabase Vs Superset
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.
Metabase Vs Redash Vs Superset
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