Likelihood to Recommend 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.
Read full review 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.
Read full review Pros 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. Read full review 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. Read full review Cons 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 Read full review 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 Read full review 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
Read full review Usability As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
Read full review Support Rating It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
Read full review Online Training Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
Read full review Alternatives Considered 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 .
Read full review 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.
Read full review Return on Investment 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. Read full review 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. Read full review ScreenShots