Apache Camel vs. Apache Hadoop

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Camel
Score 6.5 out of 10
N/A
Apache Camel is an open source integration platform.N/A
Hadoop
Score 7.2 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
Pricing
Apache CamelApache Hadoop
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache CamelHadoop
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
Apache CamelApache Hadoop
Small Businesses

No answers on this topic

No answers on this topic

Medium-sized Companies
Anypoint Platform
Anypoint Platform
Score 8.1 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
TIBCO B2B Integration Solution
TIBCO B2B Integration Solution
Score 8.5 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache CamelApache Hadoop
Likelihood to Recommend
7.8
(11 ratings)
8.9
(36 ratings)
Likelihood to Renew
-
(0 ratings)
9.6
(8 ratings)
Usability
-
(0 ratings)
8.5
(5 ratings)
Performance
-
(0 ratings)
8.0
(1 ratings)
Support Rating
-
(0 ratings)
7.5
(3 ratings)
Online Training
-
(0 ratings)
6.1
(2 ratings)
User Testimonials
Apache CamelApache Hadoop
Likelihood to Recommend
Apache
Message brokering across different systems, with transactionality and the ability to have fine tuned control over what happens using Java (or other languages), instead of a heavy, proprietary languages. One situation that it doesn't fit very well (as far as I have experienced) is when your workflow requires significant data mapping. While possible when using Java tooling, some other visual data mapping tools in other integration frameworks are easier to work with.
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Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Pros
Apache
  • Camel has an easy learning curve. It is fairly well documented and there are about 5-6 books on Camel.
  • There is a large user group and blogs devoted to all things Camel and the developers of Camel provide quick answers and have also been very quick to patch Camel, when bugs are reported.
  • Camel integrates well with well known frameworks like Spring, and other middleware products like Apache Karaf and Servicemix.
  • There are over 150 components for the Camel framework that help integrate with diverse software platforms.
  • Camel is also good for creating microservices.
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Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Cons
Apache
  • didn't work well when our developers tried to transform heavy data sets
  • Apache Camel's whole logic is based on java so team needs to have a great skill set in java
  • if there are a handful of workflows then Apache Camel's full potential can't be realized
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Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Likelihood to Renew
Apache
No answers on this topic
Apache
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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Usability
Apache
No answers on this topic
Apache
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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Support Rating
Apache
No answers on this topic
Apache
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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Online Training
Apache
No answers on this topic
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Alternatives Considered
Apache
If you are looking for a Java-based open source low cost equivalent to webMethods or Azure Logic Apps, Apache Camel is an excellent choice as it is mature and widely deployed, and included in many vendored Java application servers too such as Redhat JBoss EAP. Apache Camel is lacking on the GUI tooling side compared to commercial products such as webMethods or Azure Logic Apps.
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Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Return on Investment
Apache
  • Very fast time to market in that so many components are available to use immediately.
  • Error handling mechanisms and patterns of practice are robust and easy to use which in turn has made our application more robust from the start, so fewer bugs.
  • However, testing and debugging routes is more challenging than working is standard Java so that takes more time (less time than writing the components from scratch).
  • Most people don't know Camel coming in and many junior developers find it overwhelming and are not enthusiastic to learn it. So finding people that want to develop/maintain it is a challenge.
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Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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