A Clear Path to Data Science and AI
MapR Clarity: MapR supports running data science workloads in the same cluster as traditional analytics. This means no AI/ML silos. Users have access to all data in place from any compute profile thanks to open APIs like POSIX and container volume plugins.
- Data Science Refinery
- Blog post: Data Science Offerings from MapR
- Blog post: NVIDIA and MapR, Match Made for the AI Race
Merger Dilemma: Once Cloudera and Hortonworks merge, will you have to move your data to Data Science Workbench or IBM Data Science Experience (via Hortonworks partnership)? Why would you develop against a platform with an uncertain future for data science and AI?