Apache Superset vs. Sigma Computing

Scenarios where Sigma Computing is well suited: - Data Reporting and Visualisation : It is suitable for dashboards that integrate data from multiple back-office systems - Search and Filtering Capabilities: It provides a robust platform for searching through datasets and visualisations. Scenarios where Sigma Computing is less appropriate: Handling of null values and dynamic table adjustments

Incentivized

• Allows end users to easily dive into the data without having direct access to the table in our database management software.
• Can easily turnaround dashboards that are detailed and visually pleasing.
• Sigma is intuitive and as new features are rolled out it is easy to adopt and incorporate them into new and existing dashboards.

Incentivized

• Viewer level license is quite limited. These users can't download data or even add filters on datasets. Something to keep in mind.
• Directly querying the underlying data warehouse will lead to increased usage. Not a big deal on something like Redshift, but your Snowflake consumption will increase, potentially by a lot.

Because we are very satisfied with the product and would most likely renew because of the services it provides. It is a tool that you bring into your organization and let it change the way you analyze your data, present your data and share you date within the Respective teams

Incentivized

It has a clean and modern interface. However, it is not completely intuitive. I think it would be better and easier to navigate with more Windows style drop down menus and/or tabls. There is a significant learning curve, but that may be due in part to the technical nature of this type of software tool.

Incentivized

Yes, as long as you don’t conduct user error sigma is always up and running and waiting for you to complete your dashboards

Incentivized

It depends, it loads quickly for smaller dashboards but when loading larger amounts of data it takes more time to do so

Incentivized

They are very friendly and informative. They are quick in resolving our queries and help us understand very minute things as well. They are quick in creating feature tickets based on our custom requirements, and they would also create a bug ticket if there is any discrepancy and get that checked on time.

Incentivized

Was not involved in implementation

Incentivized

I am not an expert in any of these, though from my brief exposure to Looker it felt like a steeper learning curve, more appropriate to companies with dedicated and skilled BI engineers, whereas Sigma (and Tableau, and Looker Studio) offer a quicker and more intuitive interface for smaller companies like ours without dedicated BI resources on staff.

Incentivized

It is a cloud service offering that is able to expand based on your usage

Incentivized

• Monitoring health of cloud platform has allowed the company to anticipate issues before they affect customers – Sigma prompted us building a canary monitoring process that provides customer container health.
• Customer success has used an activity report to discover customers running runaway processes that they were unaware of, creating an alert to contact the customer and prevent an embarrassing situation.
• Customer success uses the activity report to prompt conversations regarding increases or declines in behavior that led to increasing contract limits or addressing churn concerns.

Incentivized