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Looker vs Superset: What are the differences?


This markdown code provides a comparison between Looker and Superset. The key differences between these two tools are outlined below.

  1. Data sources and integrations: Looker offers a wide range of pre-built integrations for popular data sources such as Google Analytics, Salesforce, and Amazon Redshift. On the other hand, Superset has a more limited set of supported data sources and integrations.

  2. Ease of use and user interface: Looker has a more intuitive and user-friendly interface, with drag-and-drop features and interactive visualizations that make it easy for non-technical users to explore and analyze data. Superset, although powerful, has a steeper learning curve and may require more technical knowledge to fully utilize its capabilities.

  3. Collaboration and sharing: Looker provides robust collaboration features, allowing users to easily share reports, dashboards, and insights with teammates and stakeholders. It also offers various permission levels to control access to data and restrict certain actions. Superset, while it has basic collaboration features, lacks some of the advanced sharing and permission settings offered by Looker.

  4. Customization and extensibility: Looker offers extensive customization options, allowing users to create custom visualizations, define complex calculations, and build tailored dashboards. It also supports the creation of custom applications using Looker's extension framework. Superset, although customizable to some extent, may not provide the same level of flexibility and extensibility as Looker.

  5. Security and data governance: Looker has advanced security features, including user authentication, data encryption, and access controls, ensuring the protection of sensitive data. It also provides detailed auditing and logging capabilities for compliance purposes. Superset, while it has some security features, may not have the same level of enterprise-grade security and data governance as Looker.

  6. Support and community: Looker has a dedicated support team and a large user community, offering resources, documentation, and forums for troubleshooting and learning. Superset, being open-source, relies more on its community for support, which may not be as comprehensive or immediate as the support provided by Looker's team.

In Summary, Looker offers a wider range of data sources and integrations, has a more intuitive user interface, provides advanced collaboration features, offers extensive customization options, has stronger security and data governance features, and provides dedicated support. Superset, being open-source and more focused on technical users, may have limitations in these areas.

Advice on Looker and Superset
Mohan Ramanujam
Needs advice
AmplitudeAmplitudeData StudioData Studio

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.

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Replies (1)
Ruben Lozano
Growth Marketing Specialist at Ruben Lozano Me · | 4 upvotes · 21.6K views

Hello Mohan,

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.


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Decisions about Looker and Superset

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.

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Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 306K views

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.

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Pros of Looker
Pros of Superset
  • 4
    Real time in app customer chat support
  • 4
    GitHub integration
  • 1
    Reduces the barrier of entry to utilizing data
  • 13
    Awesome interactive filtering
  • 9
  • 6
    Wide SQL database support
  • 6
    Shareable & editable dashboards
  • 5
    Great for data collaborating on data exploration
  • 3
    User & Role Management
  • 3
    Easy to share charts & dasboards

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Cons of Looker
Cons of Superset
  • 3
  • 4
    Link diff db together "Data Modeling "
  • 3
    It is difficult to install on the server
  • 3
    Ugly GUI

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