Apache Hadoop vs. Cloudera Manager

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.9 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
Cloudera Manager
Score 9.9 out of 10
N/A
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.
$0.04
Hourly rate
Pricing
Apache HadoopCloudera Manager
Editions & Modules
No answers on this topic
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
Offerings
Pricing Offerings
HadoopCloudera Manager
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsPricing 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.
More Pricing Information
Community Pulse
Apache HadoopCloudera Manager
Best Alternatives
Apache HadoopCloudera Manager
Small Businesses

No answers on this topic

No answers on this topic

Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Azure Data Lake Storage
Azure Data Lake Storage
Score 9.6 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopCloudera Manager
Likelihood to Recommend
8.0
(0 ratings)
8.5
(0 ratings)
Likelihood to Renew
9.6
(0 ratings)
8.5
(0 ratings)
Usability
8.0
(0 ratings)
-
(0 ratings)
Performance
8.0
(0 ratings)
-
(0 ratings)
Support Rating
7.5
(0 ratings)
-
(0 ratings)
Online Training
6.1
(0 ratings)
-
(0 ratings)
User Testimonials
Apache HadoopCloudera Manager
Likelihood to Recommend
Apache Hadoop (and its subsequent add-ons) are well-suited to larger, unstructured data flows, such as aggregation of web traffic or advertising. Geospatial algorithms and their outputs are well-suited for this kind of aggregation as structuring that data is challenging, but leaving it unstructured and performing queries as-needed is a better fit for most business models. With the advent of data science, I would expect Hadoop fits a LOT of their initial outputs quite well.
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Cloudera Manager is well suited for environments and deployments where the administrator user base is not well versed in the Apache Hadoop ecosystem or the Linux command line interface.
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Pros
  • HDFS is reliable and solid, and in my experience with it, there are very few problems using it
  • Enterprise support from different vendors makes it easier to 'sell' inside an enterprise
  • It provides High Scalability and Redundancy
  • Horizontal scaling and distributed architecture
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  • Cloudera Manager has an easy to use web GUI. You can start and stop cluster and services. It will start and stop services in a cluster in the right order. You can monitor the cluster, services, and physical host hardware as well.
  • Cloudera Manager has an easy to use API that allows us to create scripts to automate deployment process.
  • Cloudera Manager has an option to add additional services that you could manage via the web GUI.
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Cons
  • Hadoop is a batch oriented processing framework, it lacks real time or stream processing.
  • Hadoop's HDFS file system is not a POSIX compliant file system and does not work well with small files, especially smaller than the default block size.
  • Hadoop cannot be used for running interactive jobs or analytics.
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  • Support for third-party Python APIs within Cloudera Manager extension framework
  • Providing more reporting/logging functionality as part of the open source distribution
  • Support for the latest RHEL versions sooner in the release lifecycle
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Likelihood to Renew
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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It meets all my customer's needs.
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Usability
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
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No answers on this topic
Support Rating
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
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No answers on this topic
Online Training
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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No answers on this topic
Alternatives Considered
I feel that this is a highly reliable and scalable solution computing technology that is highly capable of processing large data sets across multiple servers and thousands of machines in a well-defined and distributed manner. Apache Hadoop can automatically scale up the number of servers and machines that are needed to process, store, and analyze data sets. It also handles explosions in data with big data technology. Apache Hadoop is good at handling all node failures as well.
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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.
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Return on Investment
  • As it was open source makes it popular choice for handling large chuck of datasets
  • It was free earlier but now it’s licensed but still enterprise is a fine tuned version which makes it easier for new users and administrators to use it
  • Our investment is worth every single penny.
  • Initial cost is more as you might need to hire administrators to setup the cluster and make them in scalable. But once done it’s pretty easy
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  • 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.
  • Increased product adoption.
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