Apache Hadoop Reviews
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Arul Mani
Real User
CEO
Mar 18 2018
What is most valuable?
HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect.How has it helped my organization?
Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it… more»What needs improvement?
Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove… more»What's my experience with pricing, setup cost, and licensing?
We normally do not suggest any specific distributions. When it comes to cloud, our suggestion would be to choose different types of instances offered by Amazon cloud, as we are technology partners of… more»What other advice do I have?
Our general suggestion to any customer is not to blindly look and compare different options. Rather, list the exact business needs - current and future - and then prepare a matrix to see product… more»Which other solutions did I evaluate?
None, as this stack is familiar to us and we were sure it could be used for such engagements without much hassle. Our primary criteria were the ability to migrate our existing RDBMS-based PoC and… more»Real User
IT Expert at a comms service provider with 1,001-5,000 employees
Jul 29 2019
What is most valuable?
The most valuable thing about this program for us is that it is very powerful and very cheap. We're using a lot of the program's modules and features because we're using software and hardware that can be difficult to integrate. For example… more»How has it helped my organization?
It helps us work with older products and more easily create solutions.What needs improvement?
We are using HDTM circuit boards, and I worry about the future of this product and compatibility with future releases. It's a concern because, for now, we do not have a clear path to upgrade. The Hadoop product is in version three and we'd… more»If you previously used a different solution, which one did you use and why did you switch?
We had a very old version of Hadoop which was already installed by another company and we upgraded it. We didn't really switch we just upgraded what was here.What other advice do I have?
I would give this product a rating of eight out of ten. It would not be a ten out of ten because of some problems we are having with the upgrade to the newer version. It would have been better for us if these problems were not holding us… more»
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Samuel Feinberg
Real User
Analytics Platform Manager at a consultancy with 10,001+ employees
Aug 14 2018
What is most valuable?
* Scalability * Parallel processing There are jobs that cannot be done unless you have massively parallel processing; for instance, processing call-detail records for telecom.How has it helped my organization?
There is a lot of difference. I think the best case is that we are able to drill down to transactional records and really build a root-cause analysis for various issues that might arise, on demand. Because we're able to process in parallel… more»What needs improvement?
In general, Hadoop has as lot of different component parts to the platform - things like Hive and HBase - and they're all moving somewhat independently and somewhat in parallel. I think as you look to platforms in the cloud or into… more»If you previously used a different solution, which one did you use and why did you switch?
There are the older relational database technologies: Netezza, SQL Server, MySQL, Oracle, Teradata. All have some advantages and some disadvantages. Most notably, they are all significantly more expensive in terms of the capital expense… more»What other advice do I have?
Implement for defined use cases. Don't expect it to all just work very easily. I would rate this platform a seven out of 10. On the one hand, it's the only place you can use certain functions, and on the other hand, it's not going to put… more»Real User
Data Scientist at a tech vendor with 501-1,000 employees
Sep 30 2019
What is most valuable?
We don't use many of the Hadoop features, like Pig, or Sqoop, but what I like most is using the Ambari feature. You have to use Ambari otherwise it is very difficult to configure. What comes with the standard setup is what we mostly use… more»What needs improvement?
Hadoop itself is quite complex, especially if you want it running on a single machine, so to get it set up is a big mission. It seems that Hadoop is on it's way out and Spark is the way to go. You can run Spark on a single machine and it's… more»If you previously used a different solution, which one did you use and why did you switch?
We used the more traditional database solutions such as SAP IQ and Data Marks, but now it's changing more towards Data Science and Big Data. We are a smaller infrastructure, so that's how we are set up.What other advice do I have?
It's good for what is meant to do, a lot of big data, but it's not as good for low latency applications. If you have to perform quick queries on naive or analytics it can be frustrating. It can be useful for what it was intended to be used… more»Which other solutions did I evaluate?
There was an evaluation, but it was a decision to implement with Data Lake and Hortonworks data platform.
Naveen Karnam
Consultant
Software Architect at a tech services company with 10,001+ employees
Mar 18 2018
What is most valuable?
High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization.How has it helped my organization?
We start with data mashing on Hive and finally use this for KPI visualization. This intermediate step not only mashes data in the form that we want through data Cube slicing, but also helps us save states as snapshots for multiple time frames. Without this, we would have had to plan another data… more»What needs improvement?
At the beginning, MRs on Hive made me think we should get down to Hadoop MRs to have better control of the data. But later, Hive as a platform upgraded very well. I still think a Spark-type layer on top gives you an edge over having only Hive.What other advice do I have?
I rate it an eight out of 10. It's huge, complex, slow. But does what it is meant for.
MahalingamShanmugam
Real User
User
Jul 17 2019
What do you think of Apache Hadoop?
What is our primary use case?
We use this solution for our Enterprise Data Lake.How has it helped my organization?
Using this solution has reduced the overall TCO. It has also improved data processing time for the machine and provides greater insight into our unstructured data.What is most valuable?
The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics.What needs improvement?
We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it.For how long have I used the solution?
More than four years.
Chitharanjan Billa
Consultant
Database/Middleware Consultant (Currently at U.S. Department of Labor) at a tech services company with 51-200 employees
Mar 15 2018
What do you think of Apache Hadoop?
What is our primary use case?
Content management solution Unified Data solution Apache Hadoop running on LinuxWhat is most valuable?
Data ingestion: It has rapid speed, if Apache Accumulo is used. Data security InexpensiveWhat needs improvement?
It needs better user interface (UI) functionalities.For how long have I used the solution?
Three to five years.What's my experience with pricing, setup cost, and licensing?
There are no licensing costs involved, hence money is saved on the software infrastructure.Articles
User Assessments By Topic About Apache Hadoop
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Apache Hadoop Questions
What is Apache Hadoop?
The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.Apache Hadoop customers
Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web LabPopular Comparisons
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