There are some issues with file retention and its stability but they can be worked through. There are a lot of things that are based on disk space that require the preparation of different and sophisticated controls. The software itself is not unstable, but sometimes its options can cause stability issues.

Apache Hadoop has good stability.

I would rate the stability a seven out of ten. There is room for improvement in performance.

The tool's stability is good.

It is far more stable than some of the other software that I have tried. It's also the current version of Hadoop software and is becoming increasingly more stable.

When a new version is released, the subsequent ones are always more stable and easier to use.

The core file system and the offline data ingestion are extremely stable. In my experience, there is a bit less stability during online data ingestion. When you have incremental online data, sometimes it stops or aborts before finishing. It is rare, but it does, but the offline data injection and the basic processing are very stable.

Typically instability is experienced due to insufficient memory, either due to a large job being triggered or multiple concurrent small requests.

Hadoop is stable because it's run on a cluster. And if some issues occur for a range of servers, Hadoop could continue its activity.

The tool's stability is good. 

In general, stability can be a challenge. It's hard to say what stability means. You're in an environment that's before production-line manufacturing, where none of the parts relate together exactly as they should. So that can create some instability.

To realize the benefit of these kinds of open-source, big-data environments, you want to use as many different tools as you can get. That brings with it all this overhead of making them work together. It's kind of a blessing and a curse, at the same time: There's a tool for everything.

 Apache Hadoop is stable.

We have not encountered any stability problems with this platform.

This solution is stable but sometimes starting up can be quite a mission. With a full proper setup, it's fine, but it's a lot of work to look after, and to startup and shutdown.

We have a three-node cluster running on cloud by default, and it has been stable so far without any stoppages due to Hadoop or other ecosystem components.

This is a stable product. 

We haven't had too many problems with stability. For the POC we used a small amount of data and we started with 10 nodes. We're gradually increasing in now to 40 nodes. We haven't seen any issues after the small teething period in the beginning. The configuration issues and the performance issues have subsided. Once we learned how to stack everything, it has been much better.

We did when we started initially with Hadoop 1.x, which did’t have HA, but now we don’t have any stability issue.

Performance is one of the reasons people choose Hadoop.

The solution is stable. It has very good disaster stability and multi-rack configuration.

The product is well tested and very stable. We have no problems with the stability of it at all. Really we just install it and forget about fussing with it. We just use the features it offers to be productive.

The solution is stable and offers good performance. It doesn't crash or freeze. It's not buggy at all.

I've never experienced any bugs or glitches.

Once we had an issue with stability, due to a complete shutdown of a cluster. Bringing up a cluster took a lot of time because of some order that needed to be followed.

The solution is stable.