MapR Pricing & Demo

MapR Data Analysis Software works to collect and synchronize data from various sources globally and helps businesses access the data easily. It comes with an additional feature of cloud storage that helps businesses sync their data in the cloud and prevent it from any cyber disasters. The quick access to data ensures higher productivity, increases quality, and yield by leveraging data at the edge. 

MapR Data Analysis Software is a software analysis platform for Dataware of AI/Analytics. Dataware is the latest technology in the IT stack that allows data to be managed as a part of a large ecosystem. The software functions as a tool for data migration, data engineering, and advanced analytics for various companies. One of its main features is the hybrid cloud that lowers the cloud costs up to 30% and avoids cloud lock-in.

MapR Pricing 

There are various editions of MapR pricing that cater to various business needs. For the exact MapR pricing, one needs to contact the vendor itself. However, the three MapR pricing plans as per the editions along with their features are given below: 

Community Edition: Includes MapR data Platform, performance measurement, and scalability.

Enterprise Edition Includes Apache Hadoop and open source projects. 

Enterprise Database Edition: Used especially in critical deployments requiring business continuity.

MapR Demo

There are interactive tutorials on the official site of MapR Data Analysis Software that imparts information about the workings and basic data analytics insights in a user-friendly manner. One can request an email with all details and understand the software.

Features-

• Get access to data from different applications. 
• Manage to lay hands on global data securely.

• Automate multi-temperature data management while preserving metadata.
• Provide transparent access to user applications. 

• Move data from one premise to the cloud seamlessly. 
• Secure data for incidents of disaster recovery, cloud bursting, etc. 

• Gain productivity by leveraging the data. 
• Get accurate results from simpler data integration 

• Support multiple processing across various applications.