MapR Scalability

MSegel
Founder at Chicago area Hadoop User Group (CHUG)
None, however when you get to a certain point in scale, you tend to hit limits in terms of hardware (disk IO and networking). This is true of all releases. Unlike the Apache releases that require Federation, MapR scales the best. As we look towards future design, scalability becomes less of an issue. You will see more of a movement towards storage/compute models and this will lead to multiple data lakes rather than a single large ocean. This is also due to potential data governance rules as well as corporate enterprise structure as well. View full review »
Alexandre Akrour
CEO at Inosense
The solution is very scalable indeed. They had a pinnable feature, based on the underlying component like Spark and they're a level five system, which I think is a clone of Hadoop, which is well managed. I'd say it was very scalable indeed. View full review »
Find out what your peers are saying about MapR, IBM, Cloudera and others in Hadoop. Updated: December 2019.
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