Cloudera Manager is a management application for Apache Hadoop and the enterprise data hub, from Cloudera. Its automated wizards let users quickly deploy a cluster, no matter what the scale or the deployment environment, complete with intelligent, system-based default settings.
$0.07
per hour CCU
HPE Ezmeral Data Fabric (MapR)
Score 9.4 out of 10
N/A
HPE Ezmeral Data Fabric (formerly MapR, acquired by HPE in 2019) is a software-defined datastore and file system that simplifies data management and analytics by unifying data across core, edge, and multicloud sources into a single platform. Just as a loom weaves multiple threads into a single piece of fabric, HPE Ezmeral Data Fabric weaves distributed data into a single enterprise-wide data layer that ingests, processes, and stores data once and then makes it available for reuse across multiple…
N/A
Pricing
Cloudera Manager
HPE Ezmeral Data Fabric (MapR)
Editions & Modules
Data Hub
$0.04/CCU
Hourly rate
Data Engineering
$0.07/CCU
Hourly rate
Data Warehouse
$0.07/CCU
Hourly rate
Operational Database
$0.08/CCU
Hourly rate
Flow Management on Data Hub
$0.15/CCU
Hourly rate
Machine Learning
$0.17/CCU
Hourly rate
DataFlow
$0.30/CCU
Hourly rate
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Offerings
Pricing Offerings
Cloudera Manager
HPE Ezmeral Data Fabric (MapR)
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Pricing is per Cloudera Compute Unit (CCU) which is a combination of Core and Memory. CCU prices shown for each service are estimates and may vary depending on actual instance types. The prices reflected do not include infrastructure cost, networking costs, and other related costs which will vary depending on the services you choose and your cloud service provider.
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More Pricing Information
Community Pulse
Cloudera Manager
HPE Ezmeral Data Fabric (MapR)
Considered Both Products
Cloudera Manager
No answer on this topic
HPE Ezmeral Data Fabric (MapR)
Verified User
Engineer
Chose HPE Ezmeral Data Fabric (MapR)
We supported all three Hadoop vendors with our Hadoop RDBMS product. Here's how I see the commercial Hadoop distribution world. If you need raw performance and don't mind proprietary technology, go with MapR. If you care about the most pure open source, go with Hortonworks. If …
It would be suited for customers who feel more comfortable with using a GUI. It is less appropriate for developers or engineers who are comfortable with command line
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.
I have not used any competitors, such as Hortonworks, because Cloudera Manager just works and meets all my customer's needs. I only have deployed Hadoop using command line, which is not easy to use and manage.
Cloudera Manager has allowed our organization to deploy Apache Hadoop to operations quicker and with less training versus using the command line exclusively.
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