Cube Dev Reviews

“This is how an ideal modern semantic layer solution should be

Pros

Building the semantic layer using CubeJS Cloud has been fantastic! It alleviates much of the development burden, which is especially valuable for small teams that lack DevOps engineers to create and monitor a platform. The development and maintenance process has been pretty simple and their support has been outstanding, resolving our issues quickly through live chat. With multiple data consumption endpoints, CubeJS makes it easy to embed analytics into our product.

Cons

Integration with BI tools still feels somewhat complicated. Some query aggregations fail and require adjustments. I also need to test the new "Semantic Layer Sync" feature. Also one feature I appreciated with dbt metrics, which I miss in CubeJS, was the ability to create a new metric based on other metrics with the same time granularity. It would be great if CubeJS could implement something as flexible as this.

“Provides excellent data driven applications

Pros

The solution offered by Cube.js has been a game changer in my development work, providing a powerful platform for building data driven applications. Its flexible data modeling features allowed me to structure data in a way that aligns perfectly with my application's needs. It processes data efficiently, giving users the ability to explore insights effortlessly.

Cons

it, like any advanced tool, comes with a learning curve. Beginners might find it difficult to understand all the concepts especially when dealing with complex data models and SQL queries. However Cube.js does offer documentation and tutorials to help ease this learning process.

“Incredible software

Pros

The Cube Cloud platform is something I really appreciate, particularly its usefulness in monitoring query performance.

Cons

I've struggled to find sufficient training resources.

“Must-have tool for modern data analysis systems

Pros

What stands out to me is the ease of creating pre aggregations, which are crucial for optimizing modern data analysis systems. Configuring and deploying them was very seamless for me.

Cons

I miss a local or systemnative optimization program, such as the cloud platform panel, that would allow me to write pre aggregations and test them before deployment. It would also enable analysis of queries and requests to further optimize my application at the data layer. This would be a valuable enhancement for the overall Developer Experience (DX).

“Fantastic headless BI tool with fantastic security

Pros

What makes cube cloud especially beneficial is its ability to integrate data models from multiple databases, along with robust security controls and support for SQL, REST and GraphQL APIs.

Cons

I sometimes come across outdated documentation.

“The intermediate layer designed for caching, fast aggregations, and abstracting queryable data models

Pros

Two particularly useful features of Cube were its ability to be queried through multiple APIs, including REST, GraphQL, and SQL. This significantly reduced the time spent on building out the data layer and allowed existing applications to easily query relevant data from Cube. And, the Cube store functions as a caching layer, not only caching queries but also providing rapid aggregations for analytics. This functionality enabled the creation of applications that met a wide variety of requirements, making it suitable for both internal and external use cases.

Cons

For a semantic layer, there are certain aspects that feel incomplete to me. This is partly by design, as Cube follows an API-first approach and focuses on doing a few things really well. However, users expecting an all-in-one solution might be disappointed. For example a semantic layer typically includes data cataloging or visualization features but Cube prefers to facilitate these rather than offering them natively at the moment.

“It's very useful

Pros

Using Cube has made generating information cubes incredibly easy and displaying them in our app a smooth process. The simple playground helps in building queries and understanding how they will function.

Cons

I find the pricing model based on the number of productive instances to be inefficient. It would be better if the subscription covered the number of productive instances without considering additional costs.

“Fast and efficient BI product

Pros

When it comes to prototyping and visualizing data, It is remarkably quick and its extensive support for our different databases and BI apps allows easy integration.

Cons

I think the documentation could benefit from more examples of different use cases.

“It surely takes your analytics to the next level

Pros

I have been using Cube for more than 2.5 years and it has provided an excellent out-of-the-box abstraction for slicing and dicing data, helping us deliver insights and analytics for our customers. Over time, Cube has added powerful query caching and pre aggregation features, which have been timely as our data volume has increased, ensuring we can still provide performant analytics to our customers.

Cons

Configuring more advanced features, such as cube store and pre-aggregations, is particularly challenging when dealing with large datasets. Seeding aggregations at the scale of millions of data points is a tough task. While Cube does provide a Slack channel for support, where you can reach out to their team and community, it seems to have been deprioritized recently. That said, Cube cloud's support team is very responsive. For production workloads, I would highly recommend investing in the managed offering after evaluating whether it suits your needs.