

1) It was written in Ruby (for us that’s a con…#JS) 2) It’s not really being maintained anymore…Īs it turns out, neither of these cons are actually too bad. In our mind, there are only two cons with Dashing. It’s designed for static monitoring of important key metrics (perfect for an e-commerce use case) and has a beautifully clean design to make that unused flat screen in your office the new centerpiece. Originally published in 2012, Dashing is a battle-tested dashboard with over 10,000 stars on Github and roughly 50 contributors. If you’ve done work in the ecommerce space in the past 5 years, you’ve probably seen Dashing in action or, at least, will recognize the patron company behind it: Shopify. Thanks Metabase team! The E-Commerce Darling - Dashing The only problem is that if you DO know SQL, you’ll probably find Metabase to be a bit limiting and might want explore more advanced options.ĮDIT: Thanks to the Metabase team for reaching out to us to clarify that Metabase does support native SQL querying when you need some extra customization. What this means from a practical standpoint is that everyone in your organization can subset tables (and even create basic charts!) without knowing any SQL. Metabase establishes data types for each column when a new table is added, so these filters are generated automatically. You start with a question like, ”How many women between the ages of 18 and 25 in either New York or LA have made a purchase in the last week?” Then use Metabase’s dropdown filters ( Gender = Female City is LA or NYC Age between 18 and 25) to answer them. Metabase is the 20% that lets you answer 80% of your questions without needing to know SQL or navigate a complicated interface.

When you’re paying for an expensive suite of tools, the majority of your work will require you to return to the same core functionality over and over again without a lot of the fine-tuning, in most cases. The Pareto Principle says that 80% of effects can be traced back to 20% of causes, and this holds true with dashboards. Each has their pros and cons (we’ll lay out both as clearly as we can) but are generally good replacements to match a more expensive tool’s use case, if not its polish. If you know what KPIs you want to track and don’t have the budget for a traditional enterprise dashboard, there are a number of open-source options with greater flexibility and affordability that we’re really excited about.
METABASE ALTERNATIVES LICENSE
Many clients of ours exploring options outside of Tableau have been quoted at $25k/year for an unlimited license or even buying “tokens” that give you per hour credit. The crazy thing is, compared to some of Tableau’s competitors, this is relatively affordable. They’re also not cheap, with licenses ranging from $500-2k/user/year. They host a massive annual conference, they’ve built their platform to run on your desktop or server, and they cater to massive and diverse organizations such as the Texas Rangers and Wells Fargo. Tableau has spent a good deal of money, time, and effort to make that the case and it shows. Most often, this presentation comes in the form of – wait for it – a dashboard.įor most businesses requiring flexible and powerful BI, Tableau is the first word that comes to mind. The problem they then face (and the new bottleneck in achieving their data goals) is how they can quickly and flexibly present this data in a way that benefits their entire team.

Their data is available and streaming in as real-time as the sources allow. All of this data tells them different things about their business and can be enriched further by combining the data in new and interesting ways. When a client comes to us, they might have weather data from OpenWeatherMap, viewership data from Streamspot, real-world presence data from Bliptrack, clickstream data generated by users from a number of apps, and partner data from an external SQL Server. We’re building a company to do just that. At Astronomer, we believe that every organization can benefit from having their data properly centralized, organized, and cleaned.
