Hitachi Lumada vs. HPE Data Fabric

Organizations may use sensors like RFID and break beams to automatically monitor components as they travel through the assembly. Real-time data from IoT may help managers and supervisors monitor the performance of their teams. With this level of transparency, bottlenecks can be identified, problems can be pinpointed, and progress can be made more quickly.

Incentivized

MapR is more well-suited for people who know what they are doing. I consider MapR the Hadoop distribution professionals use.

Incentivized

• Improve business process outcomes.
• Improve business process agility.
• Drive innovation, cost management, and revenue growth.

Incentivized

• MapR had very fast I/O throughput. The write speed was several times faster than what we could achieve with the other Hadoop vendors (Cloudera and Hortonworks). This is because MapR does not use HDFS, which is essentially a "meta filesystem". HDFS is built on top of the filesystem provided by the OS. MapR has their filesystem called MapR-FS, which is a true filesystem and accesses the raw disk drives.
• The MapR filesystem is very easy to integrate with other Linux filesystems. When working with HDFS from Apache Hadoop, you usually have to use either the HDFS API or various Hadoop/HDFS command line utilities to interact with HDFS. You cannot use command line utilities native to the host operation system, which is usually Linux. At least, it is not easily done without setting up NFS, gateways, etc. With MapR-FS, you can mount the filesystem within Linux and use the standard Unix commands to manipulate files.
• The HBase distribution provided by MapR is very similar to the Apache HBase distribution. Cloudera and Hortonworks add GUIs and other various tools on top of their HBase distributions. The MapR HBase distribution is very similar to the Apache distribution, which is nice if you are more accustomed to using Apache HBase.

Incentivized

• Data security can be improved.
• Adoption flexibility.
• Steep learning curve.

Incentivized

• It takes time to get latest versions of Apache ecosystem tools released as it has to be adapted.
• When you have issues related to Mapr-FS or Mapr Tables, its hard to figure them out by ourselves.
• Sometime new ecosystem tools versions are released without proper QA.

Incentivized

A lot of components are available and able to use what you need. Module library, Advanced analytics. Batch data processing. Variety of ways to integrate. Cost-effective. These are some of the ways Hitachi Lumada ranks above the ones we have used.

Incentivized

I don't believe there is as much support for MapR yet compared to other more widely known products.

Incentivized

• Overall cost.
• Financial/organizational viability.
• Strong services expertise.

Incentivized

• Increased employee efficiency for sure. Our clients have various levels of expertise in their deployment and user teams, and we never receive complaints about MapR.
• MapR is used by one of our financial services clients who uses it for fraud detection and user pattern analysis. They are able to turn around data much faster than they previously had with in-house applications

Incentivized