The solution is stable with no issues. Stability is rated a nine out of ten. 

We did have some breaches, but that was because we misconfigured something. Since we corrected it, we haven't had any issues. 

I would rate the stability an eight out of ten.

The solution is extremely stable.

I find GitLab to be quite stable overall. I haven't encountered significant issues with its stability and consider it a reliable platform.

I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale. 

We're happy with the stability of Azure Data Factory.

Sometimes, we experienced some instability, mainly on injection.

I rate the solution’s stability as seven out of ten.

I rate the solution an eight out of ten for stability.

The stability is dependent on how you set up your cloud infrastructure, and how you authorize people to make use of it.

The stability of Azure Data Factory is good.

I rate the scalability of Azure Data Factory a seven out of ten.

Production operation seems to run reliably so far, however, the development environment seems very buggy where something works one day and not the next. 

Everything is computed inside the SQL server if we're working with pipelines, so we have to be very careful when designing our solution in Azure Data Factory. Alteryx spoiled us because we never cared how it looked in the backend because all the operations were happening on the Alteryx server. But in Azure Data Factory, they run on the capacity of our data warehouse. So Azure Data Factory cannot run your queries, and it directly sends the query to the instance in the SQL server or data warehouse. So we have to be very careful about how we perform certain operations.

We need to have knowledge of SQL and how to optimize our queries. If we are calling a stored procedure, it joins one table in Alteryx. It is pretty easy, and we just put a joint tool. Suppose we want to do it with a stored procedure in the Azure Data Factory. In that case, we have to be very careful about how we write our code. So that is a challenge for our team because we were not looking into how to optimize their SQL queries when fighting queries from Azure Data Factory to the data warehouse.

In addition, the workflows were running very slow, the performance was bad, and some queries were getting timed out because we have a threshold. So we faced many challenges and had to reeducate ourselves on SQL and query optimization.

Overall, I believe the stability has been good, but there have been a couple of occasions when Microsoft's resources needed to be allocated were overburdened, and we had to wait for unacceptable amounts of time to get our slot. It has now happened twice which is not ideal.

This solution is stable. We are using an Azure subscription, so there is no maintenance or direct updates, it's just always the latest version.

ADF is stable. 

The solution is stable.

The stability is quite satisfactory. I would rate it nine out of ten.

It is a stable solution. Stability-wise, I rate the solution an eight or nine out of ten.

I wouldn't consider it to be stable since it fails at times.

It is a stable solution since it is a PaaS product. Stability-wise, I rate the solution an eight out of ten.

I would rate Data Factory's stability eight out of ten.

I have never experienced downtime with Data Factory. 

It is very stable.

Azure Data Factory is a stable solution. The performance is good.

Azure Data Factory is a pretty stable solution. I rate Azure Data Factory a nine out of ten for stability.

Azure Data Factory is very stable, so it's a four out of five for me. In some instances, the solution failed, but I wouldn't wholly blame Azure Data Factory because my company connected to some on-premise databases in some cases. Sometimes, you'll get errors from self-hosted integration, faulty connections, or the on-premise server is down, so my rating for stability is a four.

The product has been very stable and reliable. I'd rate the stability nine out of ten. There are no bugs or glitches. It doesn't crash or freeze. 

Azure Data Factory is a very reliable and stable solution.

This solution is very reliable.

From a security perspective, the product has come up a long way.

With the Azure Cloud Platform, in 2015, I was in a different organization and it was not reliable at all. It has become much more reliable since then and is very stable at the moment. It's reliable.

This solution is stable. 

Data Factory is stable.

Azure Data Factory is a stable solution.

The solution doesn't have stability issues. 

Data Factory is stable - I have customers running thousands of jobs a day without problems.

Azure Data Factory is a stable solution.

Azure Data Factory is a stable solution.

From what I have witnessed, the solution is quite stable. It doesn't crash or freeze. There are no bugs or glitches. It's reliable.

In the latest version, the v2 version, the solution is pretty stable. It does not give unknown letters or things like that.

The solution is stable. 

I've been happy with it overall. I don't think we've had any major issues. We've been able to do what we needed, whether connecting to different data sources or setting up different types of transformations and processes. 

The solution could be more stable. It’s touch and go. It’s not 100%.

I have found it to be quite stable. Here and there, there could be some issues and problems but overall, I'm okay with the product.

The stability of Azure Data Factory is good. The performance is good.

It has been stable. I have not experienced any issues.

We have found this to be a stable solution.

The solution is new in the market and pretty stable because ADF is a little more codified than AWS. Synapse Analytics adds another tool for data. 

Stability is not quite at the level of Informatica or DataStage. 

The stability of Azure as a PaaS could be improved.

Based on my experience with other products on the market, the stability is good. 

The tool is a stable product.

Data Factory's stability has improved following some initial issues.

I rate the stability a 9 out of 10. 

Data Factory is stable.

The stability of the product is good.  

So far it's been stable. We have not experienced any issues.

From what I've seen this is a stable solution. 

I am one hundred percent happy with the stability.

It has been stable so far.  

This is a stable solution. 

The stability of the Azure Data Factory is very good.

I would rate the stability as nine out of ten, but there are some issues with the responsiveness of the interface.

I have no issues with the stability of the Azure Data Factory. We have not had any glitches.

Occasionally, there are timeout issues that happen when connecting to the source or the target. Normally, you just hit refresh and it will connect properly.

When it comes to stability, the solution is similar to the previous Azure Synapse Analytics. They are both very easy.

On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good.

This is a stable product and we're expecting more updates from Microsoft. We have not used more than one terabyte of data so that remains untested, but for one terabyte it works fine.

Development is only done on an occasional basis, but the solution is used every day. If it is streaming data then the process is continuous, otherwise, it is initiated by the user on demand.

It is stable.

I've never experienced any issues with the solution's stability.

From what we have seen so far, the solution seems very stable.