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Looker vs Superset: What are the differences?
What is Looker? Pioneering the next generation of BI, data discovery & data analytics. We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.
What is Superset? Data exploration and visualization platform, by Airbnb. Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.
Looker and Superset can be primarily classified as "Business Intelligence" tools.
Some of the features offered by Looker are:
- Zero-lag access to data
- No limits
- Personalized setup and support
On the other hand, Superset provides the following key features:
- A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities
- An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler)
- A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user
"Real time in app customer chat support" is the top reason why over 2 developers like Looker, while over 2 developers mention "Awesome interactive filtering" as the leading cause for choosing Superset.
Superset is an open source tool with 25.1K GitHub stars and 4.83K GitHub forks. Here's a link to Superset's open source repository on GitHub.
According to the StackShare community, Looker has a broader approval, being mentioned in 71 company stacks & 7 developers stacks; compared to Superset, which is listed in 18 company stacks and 5 developer stacks.
We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.
To be honest, I don't have experience working with analytics on apps and also I don't have experience with Looker, so I cannot say I will suggest that one. I know that Amplitude is a known product analytics tool for apps. I know that in the #GoPractice course, Oleg (CEO GoPractice) was using Amplitude in all his experience with mobile game apps, so I guess apps could work well too. I have experience using Amplitude for SaaS solutions and it is great to create all kinds of analytics for the product. Then Google Datastudio is the classic solution to create dashboards and reports connect it with any data source. Also, some people, instead of Amplitude are using the new Google Analytics, @GoogleAnalytics #GA4 or Mixpanel. However, my suggestion is to use Amplitude and if there are reports that you cannot answer with Amplitude, use Google Data Studio.
I hope that could help you.
Very easy-to-use UI. Good way to make data available inside the company for analysis.
Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.
Can be embedded into product to provide reporting functions.
Support team are helpful.
The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.
Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.
And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.
Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.
Pros of Looker
- Real time in app customer chat support4
- GitHub integration4
- Reduces the barrier of entry to utilizing data1
Pros of Superset
- Awesome interactive filtering11
- Wide SQL database support6
- Shareable & editable dashboards6
- Great for data collaborating on data exploration5
- User & Role Management3
- Easy to share charts & dasboards3
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Cons of Looker
Cons of Superset
- Link diff db together "Data Modeling "4
- It is difficult to install on the server3
- Ugly GUI3