The main feature that we find valuable is that it is very fast. In terms of big data, the main feature is that the data is in so many different nodes. It goes through many data nodes so whenever we use the data, it enables us to parse the data from different data nodes.
We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time. There is some latency in the system and latency in the data caching. The main issue is that we need to design it in a way that data will be available to us very quickly. It takes a long time and the latest data should be available to us much quicked.
We don't have any problems with stability.
I'm not the one who would contact their support if we needed it.
The initial setup is straightforward.
The advice that I would give to someone considering this solution is that the quality of data has key streaming capabilities like velocity. This means how quickly you are going to refer to the data. These things matter by designing the solution. We need to take these things out.
I would rate Apache Spark an eight out of ten.
To make it a ten they should improve the speed. The data storage capacity means we can inject somewhere in the user database in more efficient ways.
