Five users, including engineers, business intelligence developers, data management consultants, and developers in my company, are using the solution.

I don't have a clear idea about the scalability of Talend Open Studio. I think Microsoft's scalability is better since you can install it on a cluster.

I did not use certain aspects of scalability to check how much I can distribute the tool in the architecture and find where we can have multiple nodes around the same ETL. I worked with one server and could run just one instance using it.

We have approximately eight people using this solution in my company.

The solution is scalable.

I would rate the scalability of this solution an eight, on a scale from one to 10, with one being the worst and 10 being the best. There are around seven or eight users of this solution in our company. Eventually, we plan to scale to 20 people.

Around four or five people, consisting of technical personnel, in my company, work with the product.

Talend operates on a clustered job server setup, available in both Linux & windows. The clusters can be scaled up with additional nodes as per demand. In the case of an on-premise setup, we assess the load and define clusters based on the load. We did not have auto-scaling.

Scalability-wise, I rate the solution a seven out of ten. I did not face any problems with the product's scalability. The tool is not very easy for a beginner to manage.

Only five engineers in my company work with the solution.

It provides good scalability capabilities.

The solution has add-ons that you can add. I'm dealing with geospatial data, and you have to have add-ons to do that, but I haven't gotten a chance to add them yet. The first add-on I tried didn't work, but I think it might just be outdated and not compatible with the version of the product that I have.

There are two of us using this solution, my colleague and myself, but in the next month or so we are going to get the Professional version in a private cloud environment. We're exploring the tool to decide if it's going to become our tool of choice for the data repository and data warehouse. Right now, we're working locally with the open-source version of it, but we're trying to decide if Talend is the right tool for us and in order to do that, we want to have the proper version of Talend in the proper environment and then do all the tests.

There are two pairs of version keys that parallelize, which is not available in the free version. However, when you can parallelize your jobs you can achieve a good degree of scalability. This is one of the points where Talend shines compared to, for example, Informatica. Informatica is designed to do one record at a time. It requires expert support and general competence in the product.

Talend, by default, can be very efficient, especially using the bulk load and bulk insert components, which, at the moment we are using. We are moving to approximately 10 terabytes of data daily. Notwithstanding the load, we had to tweak very, very little. Using standard components we could achieve our overall needs.

The tool is not scalable, but the solutions you create with the tool are.

I rate the product’s scalability a nine out of ten. Currently, we have one user in our organization. We plan to add more users in the future.

The solution has quite a good range of scalability. The jobs are quite scalable since we have now integrated them with Docker so we can follow all the principles of microservices. 

We have a license for five users. We have someone focused on data quality. Someone else is looking into the solution as a tester, and testers are working on the stewardship tool to correct the data and verify it with the business. Then there are two free developers who are solely working on the Open Studio to turn out code. 

We do have plans to increase usage.

The solution’s scalability is good. We have five users and are building ETL integration and design to implement with another system. We have three licenses for developers.

Scalability-wise, I rate the solution an eight out of ten.

Four people in my company, consisting of data engineers, data analysts, and data scientists, use the solution.

Our Talend installation has been deployed onto Red Hat OpenStack, separating out MDM, TAC, DQ, and thee job servers. I made a point of determining data storage requirements for each server, and a memory ulimit setting to match the resource profile of the components. It was trial and error but it paid off by allowing the Talend system to process large jobs of 200-300 million records over a number of hours, rather than days.

Talend Open Studio is a scalable solution.

We did some testing with the enterprise version and we did not encounter any problems with the scalability of the solution. There are scalable features available. However, the documentation could be better.

We currently have approximately 10 users who are using this solution in our company. In the future we may have plans to increase this usage but that depends on how our needs grow. It does not seem like scaling usage will be an issue.  

It can scale as needed. That's not a problem.

We have four or five users using the solution in our company. They are developers. 

This product is scalable. We have five customers who are using it.

Scalability is a good feature here.

Whether we increase usage depends on the requirements. When I started, it was the basic requirement. Now, as time passes, I'm working on competencies and the new personalities of the Talend and there are some components which are not available here which I have to download from the AppExchange. For example, there is a kind of drill component which we get from AppExchange. With the experience of five years, I have worked multiple competencies and multiple scenarios. It is scalable and customizable, but one issue we have faced individually and as a team on Talend, is the errors which are not completely recognizable. Other than that, in terms of handling, in terms customization, in terms of the UI, it is quite responsive and quite easy to use. Other than the logs.

I'm not sure how the scalability is on the solution. I personally have never tried to scale it. Our clients haven't mentioned having issues, although I don't know if they've tried to scale it out either.

We have about five people working with Talend directly in our organization.

We have never had issues in terms of scalability. In fact, we have not had requirements from any customer that the solution is horizontally scalable.

Scalability is not applicable since it is a desktop application.

I have encountered scalability issues; it requires a bit of tuning before we get to optimal performance.

Scalability hasn't been a problem.

The solution is good at scalability With their big data integration products, they're actually handling a huge data set and the scalability of it is good. They're well-positioned to scale for the client.

It's scalable because if you get to the point that you can't handle this small free software, you can have another software which is more expandable with more connectors and more functionalities. You can upgrade but you must pay. If you want to work in big data, you must use another software. Open Studio is for small use cases.

If you want to work on big data, if you want to work and analyze five or ten teradata then you need other software in this portfolio. It is scalable but you must change the software. You must upgrade this license and when you upgrade this license you get the support, you get more connectors, and you get additional functionalities. 

One developer uses Open Studio. We are two users, another colleague and me.

The solution is scalable. We did a big data integration that actually handling huge data sets, and the scalability of it is good.

It is scalable. At the moment, six or seven users are using it.

Because I am working on the open-source version, it does not make sense to assess scalability. If I were working on the licensed version then it would matter.

There are two or three of us in the company who uses it.

We have no problem with the scalability of the solution. We plan to increase usage in the future.

Scalability is quite good. 

For now, our requirements aren't that big and we didn't buy the solution for that aspect of it. If we do need to scale, we'll just add another workstation for additional jobs.