The solution is very stable with no issues so I rate stability a ten out of ten. 

The solution is stable. 

The solution is mature and stable compared to other products. 

The solution is stable. The only problem with stability would be that people are not using it efficiently.

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

The product is very stable. I've been using it for three years now, and I have projects that have been running for three years without any big issues.

The solution's stability is good. 

This solution is quite stable. We have not had any issues with stability.

It is a stable product for us. We didn't see any challenges. 

The solution is stable.

I would rate the stability a nine out of ten. I didn't face performance drops.

Databricks' stability has been great, and I would rate it eight out of ten.

I would rate the stability of Databricks an eight, on a scale from one to 10, with one being the worst and 10 being the best.

This is a stable solution in our experience.

I don't see any issues with stability going down to the cluster. It would certainly be fine if it's maintained. It's highly available even if things are dropped. It will still be up and running. I would describe it as very reliable. We don't have issues with crashing. There aren't bugs and glitches that affect the way it works.

Databricks stability is an eight out of ten because I never had issues with its stability.

Our data was not too huge. It worked well. It is easily adaptable.

It is a stable and reliable solution. I'd rate stability at eight out of ten.

The solution is very stable. There are no bugs or glitches. It doesn't crash or freeze. 

Databricks is stable.

I rate Databricks' an eight out of ten. 

This is a stable solution. 

The product is stable. It has been giving consistent outputs without any major issues.

Stability is excellent.

Databricks is quite stable. We haven't had any issues with stability. It's always working perfectly with no downtime.

It is a stable solution as long as the Microsoft Azure Platform is stable too.

The solution is stable.

The solution is stable. Microsoft offers a public service, and we can get it from the Databricks website. Additionally, many companies use it to analyze their data or create a Spark cluster to run Python or SQL scripts based on their data. I rate the stability a nine out of ten.

The stability of the solution is very good. It doesn't crash or freeze. There are no bugs or glitches. Its performance is very good.

Databricks is stable.

Stability wise, it's quite okay. In my experience, it doesn't crash.

The stability of Databricks is good.

I rate the stability of Databricks a nine out of ten.

I would rate the stability of this solution a nine out of 10, with one being not stable and 10 being very stable.

Databricks is very stable.

For now the solution seems stable. 

The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes.

This is a stable solution, especially compared to other technology on the market.

Databricks is very stable and powerful.

The solution is stable. 

Stability of the product is good, whether it's handling large volumes, diverse elements of data or processing data at speed. It has stood the test of time. It's a solution that really lends itself to that higher level of stability, versatility and diversity in terms of its capability to process different forms of data.

This solution is stable and proved very robust. When very obvious programmatic recommendations were not followed, causing memory overruns on a driver, the clusters required restarting.

It's currently stable although we have not yet tested it with a huge volume of data. We'll focus on the performance and model serving capability in the near future. We're still carrying out performance testing, developing the models and figuring out the infrastructure.

The solution is very stable. However, sometimes it intermittently restarts. I rate the stability an eight out of ten.

I would rate the product’s stability a seven out of ten.

The performance and stability of Databricks are good. It is quick and I have not had problems.

Databricks is quite popular these days and it appears to be stable. I have not found any issues with stability.

From what I know and from what I've heard, talking to our data operations team, it is stable and it's quite powerful. 

We have not found any bugs yet, although it is only the beginning of our work. I do not have enough information to say for sure.

Databricks is stable. It also helps that their support is included as part of the service.

The stability is okay now although a month after the data load there was a limitation for the first time on the project. That sorted itself out. 

Given my experience, the product is very stable. 

It's definitely quite stable, in terms of an enterprise solution. 

I'd say that it's pretty stable. 

You have these clusters running on-demand, and you can also come up with these clusters that are scheduled, and that can be run for your production jobs.

It is very hard to comment on the stability right now. We will need more time to experience the product in actual usage to render any opinions about stability accurately at that level.  

The solution is stable. I would rate the stability a seven out of ten.

Databricks is stable.

It's stable.

Databricks is stable, however, we do find some errors and don't understand what has happened. Usually, they are resolved within a few minutes. I would say it is 95% stable.

The solution has been very stable. 

This is a cluster-based solution, so it is stable.

The solution is stable.

We have found that in the development environment, Databricks is pretty stable. We have had problems where something works in development but does not work in production, and this can happen when the version is updated and certain features have been deprecated. This means that more testing is required before moving to production, but this is the only drawback that we have seen.

Basically, when we move across version we have found issues, but otherwise, it's pretty stable.

The solution is stable.

Databricks is stable.

We have not done any major implementation yet, although I think it's stable to an extent. I can't comment on it in terms of benchmark and experiencing any issues. It works seamlessly in the places where I've used it.

The solution is not exactly stable. We've faced a few bugs which have really affected it. There are bugs especially when it comes to connecting with Spark.

A couple of times I faced an issue where a long-running process was consuming a lot of time and then stopped abruptly. It necessitated starting the process again.

The solution is stable.

The solution is stable. We did not face any downtime.

I haven't heard about any major stability issues. At this time I feel like it's stable.

Databricks is very stable.