We currently have about 350 users of this solution in our company. We have different people using the tool, including data architects, data modelers, and sometimes we have business customers doing the conceptual data modeling. We have a six-person team, with two specialists and four engineers, that supports this solution. 

I haven't tested the scalability. I have hundreds of tables, but if you have thousands of tables I don't know how it would work.

No issues with scalability.

Regarding scalability, it only has two options. They should be enough, the relational and dimensional modeling. But we tried to start creating the dimensional model using the relational data that is the source. There should be some flexibility in copying and making changes in the dimensional model.

In terms of the amount of work it can handle, I have not encountered any limitation so far.

It is scalable, given that we are on the cloud. We are able to scale it up whenever we need, especially with the team server, without any issues.

We have at least 50 users who are actively working on models and using the web interface. We also have at least 30 different users who log in and look at our models, as guests. We haven't added them as users within the repository because they don't need access to it. Rather, they just use the web interface to see the models. These users intermittently come in, perhaps once or twice a week, instead of on a daily basis.

We haven't had any issues with scalability because the product works on individual workstations. We have shared licenses but everybody works on their own workstation. It's only when it goes back into the Repository that everything comes together. So, working individually is never a problem. You just need enough memory on your machine.

We've had no issues with scalability.

It seems that there would not have to be much for me to do if I wanted to expand my usage. I am the only person in the company using it at this time.

As I mentioned, I cannot upload the 3,000-table database. It cannot work with that.

No issues encountered.

The repository which is used to store the models can slow down when multiple models are added. This has improved with later releases but it is still slow at times.

No issues encountered.

I would rate the product's scalability a five out of ten. 

No issues encountered.

It seems scalable. I have had no issues. The solution doesn't differ much whether we are dealing with a small database or a large one.

There have been no issues encountered.

No issues encountered.

No issues encountered.

If you use repository, it can get slow with big data models.

I have not encountered any issues with scalability.

We haven't had any scalability issues.

No.