1. Superset Metabase
2. Metabase Pricing

There’s a broad spectrum of business intelligence (BI) tools out there, from highly technical and powerful platforms to user-friendly and lightweight dashboard builders. Choosing the right one depends on where your business is today, where you want it to end up, who needs access to the data, your tech stack, and so on.

Microsoft’s Power BI is a business intelligence tool whose main. Top industries that use Metabase for analytics are Software (11) Analytics (6) Artificial Intelligence (5). Metabase is also used in 2 other categories like Analytics and BI Platform Data Visualization etc. What are the top countries that use Metabase? Metabase has answers. Meet the easy, open source way for everyone in your company to ask questions and learn from data. Metabase is powerful analytic tool which lets anyone learn and make informed business decisions from data. Metadata is targeted as a self service BI platform for business users without IT, Database or technical skill set.

Selecting the right business intelligence tool is a lengthy, involved process that requires buy-in from many stakeholders. But the first step is getting a lay of the land and understand what the bigger players in BI have to offer.

To help you pick the right solution, we’ve rounded up ten business intelligence tools and explored what types of businesses they’re best suited for.

1. Power BI

Microsoft’s Power BI is a business intelligence tool whose main differentiator is the fact that it sits within the larger Microsoft ecosystem, integrating with Excel, Azure, Access, and more. While these integrations are a plus for many, Power BI has proven to be difficult for some to learn—and it has some unique quirks.

Who Is Power BI for?

Power BI is great for larger companies full of spreadsheet junkies that are already heavily invested in Microsoft’s ecosystem.

It’s not the easiest business intelligence tool to set up and maintain, so teams with little capacity to spare may want to look elsewhere. Once set up, it has a reputation for being more malleable than other massive business intelligence tools. One user on Quora used this comparison: Tableau is like iOS, while Power BI is like Android. The result is good modeling functionality that, again, requires some expertise to set up and utilize.

Unique Features

• Seamless integration with other Microsoft products.
• DAX (Data Analysis Expressions), Power BI’s proprietary language for modeling data. It’s powerful but takes some getting used to.

Strengths

• If you’re fully fluent in Excel, you won’t have to work too hard to understand Power BI. As Alainia Conrad of SelectHub says, “Users with experience in [Excel] will be able to adapt to [Power BI].”
• Users of Power BI tend to praise its ability to handle the flow of data as well as its modeling capabilities. In their comparison between Power BI and Tableau, user Grovbolle on Reddit says, “Power BI is very strong on the data modeling and infrastructure, a bit less on visualization.”

Weaknesses

• Power BI has a steep learning curve, and it requires expert knowledge to set up. “You need to work with an IT person to interface Power BI with existing systems,” says Shreshthi Mehta in her TrustRadius review. On G2, Xinito L. says, “This is not an application for amateurs.”
• It also has some quirks that’ll cost you time, as the good people of Reddit are quick to point out in r/PowerBI. Here is the top-rated post of all time in that community:

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2. Chartio

Chartio (Hey there! 👋) is a business intelligence tool focused on making data accessible to anyone. What sets it apart from the pack is how affordable it is and how easy it is to set up and use, even for people with no coding experience.

Who is Chartio for?

Chartio is for any company that needs an affordable yet powerful business intelligence tool that anyone can use.

The biggest, most complex companies, like New York Shipping Exchange (NYSHEX), find it “super easy to deploy” and assert that “the users get immediate value out of it.” At the same time, the scrappiest of startups, like a student-run content curation startup, can afford it and use it to improve their product.

Unique Features

• Visual SQL, a proprietary language that allows anyone to query data without knowing how to code in SQL.
• The visual form of querying allows for an intuitive drag-and-drop user interface used to build queries.
• Dynamic dashboards that can automatically update based on your queries.
• In-dashboard commenting for collaboration and presentations.
• Top-level security and HIPPA compliance for the most sensitive data.

Strengths

• There’s no need for SQL knowledge to dive into data, thanks to Visual SQL. The end business user with no coding knowledge can get the answers they need without going through the development, data, or IT teams.
• Chartio has a reputation of having** simple, fast deployment**. While he was SVP of engineering at Chartio, Arjun Anand led the charge for setting up Chartio. About his experience, he says, “With Chartio, it only took a day to get everything going, and then a week to get the initial dashboards to show what we could accomplish.”
• Because it’s so easy for end business users to set up and use, Chartio frees up data and development teams to do the work they should be doing. In his G2 review, Dan D. says, “Chartio’s SQL GUI (graphical user interface) enables end users to help themselves, freeing up huge amounts of resources that can be redirected onto other projects.”

Weaknesses

• Chartio prioritizes end usability above most other things. This means that there are a few features it needs to develop in order to satisfy the most hardcore of data analysts.
• Jason Harris at Panoply explains it this way: “While [Chartio] may not have all the functionality that your data analysts are looking for, it’s well suited to business users.” On G2, one executive in financial services says, “[Chartio] has relatively fewer features than the other primary tools out there, like Tableau. I think in part, that’s what enables it to be user-friendly, so it’s a trade-off rather than a downside.”

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3. Looker

Looker is a powerful tool for modeling data using its proprietary language, LookerML, that has limited visualization capabilities and data inputs. Google Cloud Platform acquired it in 2019, moving it into the Google walled garden, which means it may get combined with Google Data Studio in the near future,as explained in-depth here. Download itl port devices driver.

Who is Looker for?

Looker is built for data teams that need powerful modeling capabilities above all else.

These teams also need the patience to learn Looker’s propriety language, LookerML. That said, Looker has a robust library of analytics code called Looker Blocks, which can speed up repetitive workflows once up and running.

Unique Features

• Looker Blocks®, pre-built analytics code that provides a jumping-off point for your own data modeling.
• LookML, Looker’s proprietary data modeling language.

Strengths

• LookML provides a powerful modeling layer that some veterans enjoy. On Reddit,user rlaxx1 says, “The modeling layer allows you to basically turn SQL into object-oriented code.”
• Presets like Looker Blocks® that can help your team get off the ground quicker if they know SQL inside and out.

Weaknesses

• What Looker gains in modeling capabilities, it loses in its ability to manipulate and visualize data. On Quora, Bill Ulammandakh says, “Expect to be able to do maybe 1% of what you can do in Excel in terms of data manipulation.”
• Also, despite its strengths in modeling, some find it time-consuming to prepare data for Looker. “You do need a preparation software before you use it, which means you’re not able to cleanse and prepare your data before connecting to a data source,” says Amrita C. on G2.

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4. Google Data Studio

Google Data Studio is a data visualization tool from Google with easy integrations to the entire Google ecosystem, from Google Analytics to Google Sheets to BigQuery. The amount of integration and the fact that it’s free make it easier for more people to get into, but its visualizations and formatting are often lacking.

Also, Google’s acquisition of Looker makes some people wonder about the future of Google Data Studio.

Who is Google Data Studio for?

Google Data Studio is good for people who have bought in to the Google ecosystem and want to visualize data quickly.

Google Data Studio has perhaps the lowest bar of entry for the business intelligence tools listed here. But it lacks deeper data functionality, relying on other Google services like BigQuery to fill in the gaps.

Unique Features

• Seamless connection to Google products makes it easy to connect data across Google’s ecosystem.
• A large library of reporting templates suited for many use cases.

Strengths

• If you have a Google account, you can start right away.
• Because it’s easy to get Google Data Studio up and running, it has a large number of users, from students to hobbyists to companies alike. This user base provides great community support.

Weaknesses

• Google Data Studio is part of the Google walled garden, so third-party integrations will always be an issue because Google wants you to only use Google products with Google Data Studio.
• Also, even with its low bar of entry, Google Data Studio can make it difficult to format reports. Matthew O. on G2 says, “I’d like to be able to use a highlight tool to mark important KPIs in my tables, but I’m not able to do that. Or… when I want to have bold text in certain places, there’s no way to do it.”

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5. Tableau Desktop

Tableau Desktop is the standalone data visualization tool from Tableau, a legacy giant among other business intelligence tools. Tableau was one of the first BI tools to lower the bar for entry into data visualization but still remains out of reach for the average business user due to its older feature set designed for large, expert data teams.

Who is Tableau Desktop for?

Data scientists and analysts who need the power to create custom, dynamic charts and complex visualizations.

Tableau’s older feature set makes it robust, but not very agile. It’s often used as a base-level data tool that only a few people in the company know how to use well.

Unique Features

• Tableau allows teams to join data from multiple databases.
• Its depth of features make it useful to data scientists, analysts, and developers alike, but not the average business user.

Strengths

• Tableau has a vast user base that provides a lot of community support.
• It’s very flexible in how you manipulate and use data, making it a powerful data visualization tool. One Capterra reviewer says, “The quality and variety of graphics that can be created with Tableau is vast, and that’s the best part of it.”

Weaknesses

• Tableau is very difficult to pick up for most business users, which leads to situations as described by user adventuringraw on Reddit: “The Tableau guy in my squad is in HIGH demand, there’s multiple teams fighting over him. God help him if he ever wants to do something other than Tableau, haha.”
• While Tableau has some very good legacy BI features, like visualization, it lacks some important features other business intelligence tools have innovated that have become fairly commonplace. Tristan Handy, CEO & founder of Fishtown Analytics, puts it this way: “Tableau, for all its impressive visualization capabilities, can’t really deal with production data: its drag-and-drop capabilities just don’t allow users to express the complicated business logic that is required in real-world BI.”

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6. Sisense for Cloud Data Teams (Previously Periscope Data)

The recently renamed Sisense for Cloud Data Teams is a business intelligence tool designed with SQL experts in mind. It can help your team move more efficiently—provided you have a deep knowledge of your data and SQL.

Who is Sisense for Cloud Data Teams for?

SQL veterans looking to speed up their data analysis workflow.

Sisense for Cloud Data Teams is an enterprise tool for companies with sophisticated data teams. It’s useful for teams that use SQL, Python, and R regularly to make sense of business data.

Unique Features

• Ad-hoc analysis, where you can create reports and visualizations on the fly.
• You can use SQL, Python, and R on the platform.

Strengths

• It has macros that make exploring your company’s data with SQL a little easier. Bala Parthasarathy, CEO and Co-founder of MoneyTap, says, “You can write regular SQL, of course, but these macros make it easier to turn marketing guys and product people into basic SQL programmers.”
• Also, if you know SQL very well, it can speed up your workflow. “I like the speed and streamlined SQL language it enables. SQL knowledge is required, so this is not meant for the casual business user,” says one reviewer on Capterra.

Weaknesses

• If you don’t know SQL, Sisense for Cloud Data Teams is very limited. A reviewer on G2 says, “If you have a lot of people who do not know SQL but want to explore the tabular data themselves, this is probably not the tool for you because the ‘Data Discovery’ tool is very basic.”
• It’s not well suited to companies just starting to get a handle on their data. “If your volume of reporting and metrics is not at [10,000 clients with an average of a couple hundred data points per client] yet, it may not be as useful (or, rather, may overload you with information that distracts from your specifics),” says a reviewer on TrustRadius.

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7. Domo

Domo is a business intelligence tool that made waves early on in its life when it was awarded unicorn status. As it grew into a BI industry giant, it attracted its fair share of fans and detractors.

Who is Domo For?

Enterprise businesses looking to get a handle on what’s happening with their data day-to-day.

In particular, Domo targets the busy executive with its mobile-first philosophy and its segmentation tools by team. It’s good for large companies looking for data distribution over data analysis that can afford the sticker price and the time spent to get Domo’s system fully up and running.

Unique Features

• Domo’s mobile-first philosophy connects all BI data to your phone, providing alerts based on what’s most important to you.
• Features are split out into modules for each team into what Domo calls the “Business Cloud.”

Strengths

• Domo’s integration game is strong as one G2 reviewer says, “It has a huge range of plugins that we can connect quickly.”
• Its module system allows many different teams to access the data. “It is a very flexible platform where we can see everything that happens in [each department],” says project analyst Isabella on Trustradius.

Weaknesses

• As of late, Domo’s customer service has not received good reviews. User GeneralDouglasMac on Reddit says, “I would NOT suggest DOMO.** It has fallen by the wayside in support, feature matching, and costs** compared to every other tool out there.”
• Domo has also gained a reputation for leaving new users high and dry once they’re on board. One Capterra reviewer says, “As soon as you sign that contract they wash their hands of you … so unless you have a team of SQL coders to build everything by hand, or are prepared to pay Domo’s extortionate professional services fees (which you’ll need to book weeks in advance), you should avoid this product.”

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8. Mode Analytics

Mode Analytics is a data science platform with some business intelligence capabilities designed for large enterprise companies. Its main target users are data scientists and analysts with a lesser emphasis on the end business user.

Who is Mode For?

Data scientists looking to make their analysis and models more accessible to the larger organization.

And by larger, we do mean larger. Mode is not a small BI tool, and according to some clients we’ve talked to, it’s really gunning for the Fortune 500 crowd.

Unique Features

• Notebooks, which allow you to use R and Python to do data science.
• Helix data engine, which allows you to use SQL, R, Python, HTML, and CSS to develop reports.

Strengths

• If you have SQL knowledge, Mode can provide access to deep data science capabilities.
• Thanks to its Python capabilities, data scientists tend to find it very versatile. On the r/datascience subreddit, user JoyousTourist says, “I really enjoy using Mode Analytics because I can query data directly from multiple MySQL databases and then merge them into a Python notebook and display visualizations in a report.”

Weaknesses

• Mode is for data scientists and high-level data analysts first (to the detriment of the end business user) and even some lower-level analysts. On Capterra, Ifabiyi A. says, “For someone less technical,** it isn’t the easiest to build dashboards** with inputs and make my queries more user-friendly for my teammates.”
• Data visualization is limited if you don’t want to custom code each report. “You cannot easily change legend color without either rewriting your SQL code or using HTML. You cannot change the x / y axis of the data without advanced manipulations,” says Steven M. on G2.

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9. Klipfolio

Klipfolio is a business intelligence tool best suited for dashboard data visualization. It focuses solely on making dashboards easy to create and maintain (to the point where some people don’t consider it a full business intelligence tool).

Who is Klipfolio For?

End business users looking to quickly build dashboard reports.

Its laser focus on dashboard tools makes it a lifesaver for some, but a major pain for those looking todive deep into data. For companies with a solid data infrastructure already in place, it may be a good fit to help business users visualize data, but it’s not for those who need a tool dedicated to data.

Unique Features

• A library of pre-built Klips, Klipfolio’s proprietary XML files, which allow you to quickly assemble dashboards.
• It has a mobile app, so you can check your dashboards on the go.

Strengths

• Klipfolio is good for displaying live data. A reviewer on TrustRadius says, “Klipfolio is an excellent tool for basic to intermediate data visualization / dashboarding. It is best used for live display of data from various sources in a consistent interface.”
• Its library of Klips makes it flexible enough to fit most companies’ specific goals. “There are many different charts, tables, and other views to show your KPIs, and it is a great tool to share with your team and keep them motivated to achieve the objectives,” says Erika A. on G2.

Weaknesses

• Klipfolio is a dashboarding tool, first and foremost. It’s not a robust, fully-featured BI tool.
• Despite its user-friendly look, it’s not easy to set up. Reddit userMephiXanadu complains that “It looks like it could theoretically be useful, but it’s IMPOSSIBLE to set up if you don’t have an extensive background in coding/Excel.”

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10. Metabase

Metabase is a free, open source BI tool focused on analytics and answering day-to-day business questions. It’s bare-bones, and even though it’s fairly intuitive once up and running, it can still leave SQL veterans behind.

Who is Metabase For?

Companies that need an affordable tool their data analysts can use to answer common business questions.

Metabase is best suited for teams that know exactly what they want and how to get it. Because it’s open source, Metabase has little-to-no customer support, so it’s up to you to get it right.

Unique Features

• Metabase is free, offering many powerful capabilities for, well, free.
• It’s open source, and you can host it yourself, meaning it’s fully under your control.

Strengths

• If you really know what you’re doing, you can make Metabase just about as powerful as any of the business intelligence tools on this list.
• Its open source and self-hosted nature makes it very secure, highly customizable, and completely under your control.

Weaknesses

• Metabase’s bare-bones quality makes it difficult for non-technical users to get up and running. Even technical users can have trouble.
• It can also leave behind power users, as Peter Weinberg of Panoply says: “Advanced SQL users may find it tricky to learn the SQL-but-not-quite style data interface, but it’s not designed for them.”

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Choosing the Business Intelligence Tool to Meet Your Needs

All the business intelligence tools listed here have some form of a free trial, so it’s easy to dive in and try them out. Each has its strengths and weaknesses, but we encourage you to try out as many as you can. We guarantee one will feel much more natural to your business than the others.

While you’re here, you might as well start with Chartio. Xemtec usb devices driver.

With its most recent IPO that took the whole Wall Street by storm, everyone in the data market space is talking about Snowflake - a cloud-based data warehouse-as-a-service.

As companies are eagerly switching from traditional server-based data warehouses to modern server-less ones (as described in detail by Lars Kamp in his letter to his investors), it's very likely that your company is looking at adopting Snowflake and revamping the complementary data stack.

In response to this movement, as a data analyst/engineer, you set out to find the most compatible BI and reporting tools for this data source.

Although Snowflake has kindly listed out all BI tools that it can inter-operate with, it is not enough for us to simply decide which one fits our company's demand for data.

This blog will give you a detailed comparison of the top 5 Snowflake BI & reporting tools, which hopefully will give you some pointers to choosing the most suitable one for your current data stack.

1. Holistics
2. PowerBI
3. Looker
4. Tableau
5. Metabase

Holistics

Holistics is a self-service BI tool that lets data analysts model and transforms data in Snowflake and many other SQL data warehouses. Then, non-technical users can run their own analysis to insights without having to rely on the analysts any more.

Holistics is best-known for its data modeling capability, which can help analysts create a single source of truth where you can apply business logic to your own data and make sure it is accurate, maintainable, and re-usable.

You can learn how to connect Holistics to Snowflake in their detailed guide here.

Pricing

Holistics generously offers a free plan after your 14-day trial expires, which does not charge you based on the number of users, but on the number of query runs. That means, if you are a bootstrapped startup with limited budget, Holistics is the right tool for you. It will only start charging as your company and its analytics need scales up.

Holistics starting price of $200/month is impressively affordable when compared to almost all competitors on the market, especially when its features are equally powerful and plentiful. Even if your company scales up with more analysts joining the data team, you will not need to worry about cost per additional head count.

Pros

• Allow you to query the Snowflake database using customizable SQL queries and get fast results with its cache layer
• Materialized views of query results are stored back to your own SQL database, for immediate access and fast visualizations and reports.
• Automated scheduling of reports and dashboard with the latest data in Snowflake, sent directly to your email inbox.
• Advanced SQL Editor: Version History, Autocomplete, SQL Snippet, Highlighting, Auto-formatting, Query History, Custom Advanced Logic..
• Drag-and-drop interface for business users to explore data and generate reports to answer ad-hoc questions.
• Competitive pay-as-you-go pricing model, which only scales as your company scales.

Cons

• Though powerful, Holistics is a fairly new tool to the market. A lot of advanced features are still on their roadmap.
• Holistics has not supported Git-integration and version control, which is preferable to a lot of advanced analysts.
• Dashboards are not as interactive as other competitors'. Currently Holistics only supports drill-down by date and drill-through to another dashboard.

PowerBI

PowerBI is quite well-known in the BI industry, especially for enterprises that adopt the Microsoft ecosystem. It supports an impressive number of data sources, giving companies the power to centralize their data in one place.

PowerBI has a user-friendly interface with amazing data visualizations capabilities, ranging from simple dashboards that analyze eCommerce metrics to highly complicated ones like the NFL Football analysis one below.

Connecting PowerBI to Snowflake is fairly simple. You can follow the instructions here.

Pricing

PowerBI pricing is also attractive for small-scale companies with small data teams. If you're an individual and only need PowerBI on your local computer to do analysis, then you can download the desktop version for free. However, if you want to use more Power BI services and publish your reports on the cloud, you can take the Power BI Cloud service solution for $9.99 per user per month.

Please note that if your company is concerned about security and on-premise deployment, the price goes up considerably at $4,995 per month, with an annual subscription.

Pros

• Support hundreds of data sources, from cloud service like Snowflake to offline files like Excel
• Powerful data visualization capabilities. Besides the basic visualization types, PowerBI allows advanced users to choose from a market place of custom visuals or create their own using well-known Javascript libraries
• Frequent updates and innovations. Follow PowerBI's blog and you will see the team is really active in pushing new features and changes.
• PowerBI has an active community of power users and employees who are willing to deep dive into your use case to help you out.

Cons

• PowerBI has a steep learning curve. Data analysts must learn DAX (Data Analysis Expression) language to fully leverage PowerBI's power, which is complicated and rigid sometimes.
• Limited data delivery capability. If you want to view a PowerBI report, you must have PowerBI desktop installed or have PowerBI Report Server already setup. This is difficult for Mac users since PowerBI can only be installed on Windows devices.

Looker

Superset Metabase

Recently joined as a part of Google Cloud Platform, Looker is a powerful BI tool that provides an innovative approach for real-time data exploration and analytics.

Looker has powerful dashboard capabilities that can cover most data discovery use cases. However, unlike Power BI, it requires a full semantic model for storing all your business logic and metrics without having to add multiple versions of a slightly different metric to your database tables. That means you cannot just take Looker, point it at a database, and get your visualizations in minutes. It requires an upfront definition using their own language LookML, which will take a considerable amount of time to master.

To connect Looker to Snowflake, follow the instructions here.

Pricing

Looker does not publicly release its pricing information because they will customize for each company. From my conversations with a few Looker users, the price could range from $3000 - $5000 per month for 10 users with an annual subscription. As I mentioned above, Looker is designed for companies with mature and dedicated data teams that are willing to adopt a completely new modeling language and spend time setting up Looker to fit their whole data stack.

Pros

• Looker runs entirely in-browser, so there’s no need for desktop install and it's better for collaboration and data delivery between internal and external users
• Looker operates entirely on the data in your database. That means that you’re operating directly on your full dataset and getting all the horsepower of your database, whether that be an MPP like Vertica, Redshift, Bigquery; a SQL-on-Hadoop setup like Impala or Spark; or a standard RDBMS like MySQL or Postgres
• Automated reporting - Looker allows you to schedule emails for daily/weekly/monthly reports or send alerts if there are anomalies in data.
• Looker has GitHub integration, so you can see every change made to the modeling layer and combine the work of multiple developers seamlessly

Cons

• Looker has a steep learning curve when it comes to adopting a new language (LookML) & the model-view approach for the end-users. You definitely need to have an internal team that is dedicated to just setting it up and getting the rest of the people on board.
• Being locked in the platform. LookML takes over most of the work of preparing tables for visualization. Moving from Looker to another visualization tool will require additional work to migrate everything that has been defined by LookML.
• Although Looker provides a large library of custom charts, it can be very difficult to customize the visualizations to your exact need.

Tableau

Tableau is most famous for its unparalleled capabilities of visualizing information. The application’s data visualizing quality is superior to what Tableau software competitors offer. If you want to create complicated dashboards with seamless interactivity, Tableau is definitely the must-have tool.

To connect Tableau to Snowflake, read more here.

Pricing

Tableau pricing is fairly complicated and is charged both based on your use-case and number of team members. Moreover, Tableau also charges based on the roles of users, with a Creator costing $70/month, an Explorer $35, and a Viewer $12. Since this number is dependent on your business, you really should plan ahead and prepare for an upsurge of additional cost if you decide to purchase Tableau.

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• Great visualization capabilities: a large library of charts and highly interactive dashboards
• Tableau's friendly interface allows data analysts of all experience levels to quickly begin producing compelling and useful analysis and visualizations.
• Tableau handily deals with millions of rows of data, from various data sources, including spreadsheets and SQL databases. This allows users to integrate disparate data sources that may have been difficult to connect otherwise.

Cons

• Like PowerBI, Tableau cannot handle too big a dataset. It will get very slow. If you import data from multiple sources and the data is huge, it sometimes tends to lag crash.
• Lack of BI capabilities. Tableau lacks functionality required for a full-fledged business intelligence tool, such as large-scale reporting, the building of data tables and static layouts.
• Tableau Desktop lacks the basic functionality of cleaning and prepping the data to be imported in Tableau Desktop. This is one of the major features which it lacks, you need additional support from Tableau to get these things added.

Metabase

Not as equally popular as Holistics, PowerBI, or Tableau, Metabase is an open-source tool designed for non-technical users to provide big data insights and visualizations.

Metabase is best for businesses of all sizes that want to deploy either cloud-based or on-premise versions. You can use Metabase for KPI monitoring, database management, bug tracking, record filtering, debugging, and query builder.

Metabase does support connecting to Snowflake, but you might want to take into consideration a few things.

Pricing

Free

Metabase Pricing

Pros

• Metabase is free and open-source. Metabase is licensed under GPLv3 with source code available on GitHub, which you can use to deploy on your own server and maintain on your own.
• Metabase is lightweight to install.
• The UI is simple and friendly so it takes little training to use the tool effectively.

Cons

• Metabase only works well with a single SQL data source. If you have data from multiple sources, chance is you might want to find another tool because it does not allow you to join table data.
• Despite having the desktop version, Metabase sometimes gets very buggy and slow to render the results.
• Contrary to Tableau, Metabase has limitations regarding customizing how the charts look.
• Because it is self-hosted, companies must handle the administration issues and app updates on their own, which might take a lot of time and effort.

Any of the five tools mentioned above will work well with Snowflake, but not all of them are suitable for your company.

Sometimes, the most powerful, feature-rich tool might not be the best choice, as it comes with too high a price or too steep a learning curve.

Therefore, if you're an analyst tasked with finding such tool, a good advice is to involve a lot of your colleagues and end-users to use the product intensively during the free trials. You will then understand the real bottlenecks of each tool and make the wisest choice.

If you need a little more pointer to choose the right tool, you might want to check out Chapter 4 in The Analytics Setup Guidebook which will discuss in detail how you can navigate the Business Intelligence tool space.