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Cube.js vs Looker vs Metabase: What are the differences?
Introduction: When comparing Cube.js with Looker and Metabase, it's essential to understand the key differences in functionality and features to make an informed decision on selecting the right tool for your analytics needs.
Architecture: Cube.js is an open-source analytical API platform that allows developers to build interactive analytics features quickly, while Looker and Metabase are BI tools that provide a more user-friendly interface for non-technical users to create ad-hoc reports and visualizations. Cube.js focuses on customization and scalability, whereas Looker and Metabase offer more out-of-the-box solutions.
Data Source Connectivity: Cube.js is more flexible in terms of data source connectivity, allowing users to connect to a wide range of databases and services such as BigQuery, Redshift, and Elasticsearch. Looker and Metabase also support multiple data sources, but they might require additional setup or configurations to connect to certain databases.
Customization and Embedding: Cube.js provides extensive customization options to tailor analytics features to specific business needs, including embedding analytics directly into existing applications. Looker and Metabase offer some level of customization but may not be as flexible as Cube.js in terms of embedding analytical features.
Community Support and Documentation: Cube.js has a growing community of developers contributing to its ecosystem and providing support, whereas Looker and Metabase have more established communities and comprehensive documentation for troubleshooting and learning resources.
Cost Structure: Cube.js is open-source and free to use, making it a more cost-effective option for organizations looking to implement custom analytics solutions. Looker and Metabase have commercial pricing models based on users and data usage, making them potentially more expensive for larger deployments.
Scalability and Performance: Cube.js is designed for scalability and performance, allowing for fast query processing and handling large volumes of data efficiently. Looker and Metabase can also handle large datasets, but Cube.js may offer better performance optimization capabilities for complex analytics use cases.
In Summary, understanding the key differences between Cube.js, Looker, and Metabase in terms of architecture, connectivity, customization, community support, cost structure, and performance scalability is crucial for selecting the right analytics tool for your organization.
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.
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.
Cheers,
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 Cube
- API8
- Caching6
- Open Source6
- Visualization agnostic6
- Rollups orchestration4
Pros of Looker
- Real time in app customer chat support4
- GitHub integration4
- Reduces the barrier of entry to utilizing data1
Pros of Metabase
- Database visualisation62
- Open Source45
- Easy setup41
- Dashboard out of the box36
- Free23
- Simple14
- Support for many dbs9
- Easy embedding7
- Easy6
- It's good6
- AGPL : wont help with adoption but depends on your goal5
- BI doesn't get easier than that5
- Google analytics integration4
- Multiple integrations4
- Easy set up4
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Cons of Cube
- Incomplete documentation1
- Doesn't support filtering on left joins1
- Poor performance1
- No ability to update "cubes" in runtime1
- Cannot use as a lib - only HTTP1
Cons of Looker
- Price3
Cons of Metabase
- Harder to setup than similar tools7
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