HPE Ezmeral Data Fabric (MapR) vs. Kognitio

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

Incentivized

What you have are different strategies for data encoding, which makes the process quite flexible, it is perfectly done so that a joint and collaborative work can be carried out, this information analyzed in large quantities, is extremely vital for the company, by giving it the correct and timely reading

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

• Ultra fast query results.
• IN Memory Database.
• Easy integration to reporting services.

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

• Problems Could Be Encountered is particularly pronounced in more complex analyses.
• Categorical variables are often not precise enough

Incentivized

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

Incentivized

We selected Kognitio because of the legacy systems that are still running. Also, we have legacy systems in place that are fit for Kognitio. End-user has good feedback on our side when we started implementing this solution. Current servers are compatible with Kognitio in place.

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

• The implementation of the formats to integrate the users we have and the program is also good.
• I also improve the control of aspects related to the work environment

Incentivized