Databrain vs. Metabase : Detailed Comparison
Explore the differences between Databrain and Metabase to make an informed decision for your data analysis and visualization needs.
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Introduction
Metabase:
Metabase is a business intelligence tool, predominantly tailored for internal business analytics. It has capabilities for embedded-analytics but is designed for data professionals.
Databrain:
Databrain is purpose-built for SaaS applications. It prioritizes tackling embedded-analytics pain points like customizability and performance. It operates on a no-code framework, enabling anyone in the org, from PMs to Developers, to easily create metrics and build dashboards.
Implementation Ease:
Metabase:
- Metabase embedding demands technical expertise and code-level changes to deeply embed into SaaS applications.
- Integration is facilitated via iFrame.
Databrain:
- Databrain offers plug and play connectors directly to your app using APIs and plugins.
- Advanced configurations, like multi-tenancy and security features like RLS are enabled off the bat.
- You can have your whole analytics module up and running in a day.
Tailored to Fit(Customization):
Metabase:
- Provides only a basic design toolkit in its UI, as it was primarily built for internal analytics.
- Advanced customization requires technical knowledge.
- Metabase forces you to choose a higher paying plan in order to enable it’s white-labeling options.
Databrain:
- Databrain offers extensive customization options down to the chart prefix and suffix level, all via the UI itself.
- Using its drag and drop approach, dashboards and reports can be built and customized by anyone in the org, without any technical knowledge.
- Databrain offers full white-labeling on all its plans.
Flexibility:
Metabase:
- Metabase's integration is somewhat restricted, primarily relying on iFrame, which can occasionally compromise on performance and compatibility with host applications.
Databrain:
- Databrain exhibits strong integration capacities, compatible with React, Vue, Angular, or Svelte.
- Its web components approach to embedding offers superior adaptability when compared to Metabase, and is also fully programmatic giving you full-control over the embedded dashboards and reports.
Data storytelling and insights:
Metabase:
- While Metabase supports custom reporting, its alignment is more towards seasoned data analysts, potentially limiting accessibility for the broader user base.
Databrain:
- One of Databrain's premier features is its tailored reporting or self-service analytics. This functionality empowers users to create and modify views and dashboards, in a no-code environment, enabling anybody to view and generate insights using their data.
Pricing:
Metabase:
A common misconception is that since Metabase is open-source, it is free. Metabase actually offers 3 priced plans and its free-plan is applicable only on its self-hosted version which does not come with any white-labeling or embedding options. There is no dedicated support channel and users have to troubleshoot themselves and search forums for answers. Embedded analytics is only available on its enterprise-plan which starts at 15k USD a year and varies based on the number of users.
Databrain:
Databrain offers 2 plans - growth and enterprise. Both plans enable you to have unlimited users and workspaces promoting fully transparent pricing that remains predictable even as you scale to a company with 1000+ customers. Both plans offer full white-lablelling features and their pricing starts at $833 per month, for unlimited users.
Comparison table: Metabase vs. Databrain
Conclusion:
Databrain offers a larger feature set to Metabase. However, Metabase is open source and Databrain is not. For companies looking for an scalable analytics solution that offers full white-labeling, enterprise-grade performance and a tool that can get you up and running fast, Databrain appears to hold a significant advantage.