RStudio Connect Reviews

Neutral

We use the solution for statistical modeling.

The solution offers ease of use, affordability, cloud options, and many open sources, like integration with control over the lobby, using package managers. It has a flexible database like Postgres SQL for metadata, audits, logs, etc.

Our model has used various tools together. It should make sense for them to use these tools in conjunction with RStudio Connect. Currently, they use none or only PSN and a couple of other devices. There should be integration with these tools or the ability to integrate various statistical tools, both open source and proprietary, with RStudio Connect.

RStudio Connect should ideally provide an add-on library where modules can be utilized. There's no need to introduce something entirely disconnected but beneficial for statistical modeling. If some popular tools they use, such as Norman or PSF, were bundled and made available as add-ons, it would create a centralized place. This centralized platform would allow individual vendors to ensure compatibility of their products with RStudio Connect and provide them on the marketplace. Customers could then choose these validated additional tools, integrating them seamlessly with RStudio Connect.

I have been using RStudio Connect for a couple of years.

The product is stable.

I rate the solution’s stability an eight out of ten.

Scalability becomes a non-issue if RStudio Connect is hosted on the cloud and provided as a SaaS solution, such as a robust cloud service. The infrastructure is managed seamlessly without concerns. However, considering its integration as a component within platforms like Azure's marketplace, the challenge lies in containerizing it for deployment as a scalable containerized solution, allowing for multiple instances.

100 users are using this solution. If it is successful, there is a lot of potential.

The technical support still has to improve. There are different cases where both response time and quality were poor. You had some queries about things, and the quality of the response took some time because they couldn't understand what you were trying to ask.

We have tried SAS. We switched to RStudio because it uses R, which is open-source.

The initial setup is very easy.

The product is not very expensive. When the number of licenses grows, the procurement team should come in and negotiate to get a better price and discount.

I rate the product’s pricing a three out of ten, where one is cheap, and ten is expensive.

As an enterprise architect, I observed various user groups and conducted capability mapping exercises. Through interviewing these diverse user groups, I recognized a strong potential in consolidating them onto a unified platform. Three years ago, I brought them to RStudio Connect. However, instead of utilizing the task option, we opted for a local installation. To handle large model processing, we provisioned a dedicated service server allowing up to four users to simultaneously log in and execute their modeling jobs. Nevertheless, this approach now seems somewhat outdated—a legacy method. We aimed to explore alternatives rather than solely relying on infrastructure to bolster our large-scale computational capabilities. Upon evaluation, RStudio Connect appears to be a promising solution due to its robust capabilities.

RStudio Connect has its utility, and Databricks is supposed to be used in a different way. RStudio is for the functions and features you need to model, whereas Databricks is more for an analysis plot form where we can do a big data analysis.

RStudio is a great tool. Many people should be using it. SAS has its utility. It has become the SAP of the ERP.

Overall, I rate the solution an eight out of ten.