Likelihood to Recommend
- Less appropriate for small data sets
- Works well for scenarios with bulk amount of data. They can surely go for Hadoop file system, having offline applications
- It's not an instant querying software like SQL; so if your application can wait on the crunching of data, then use it
- Not for real-time applications
- Hadoop is a very cost effective storage solution for businesses’ exploding data sets.
- Hadoop can store and distribute very large data sets across hundreds of servers that operate, therefore it is a highly scalable storage platform.
- Hadoop can process terabytes of data in minutes and faster as compared to other data processors.
- Hadoop File System can store all types of data, structured and unstructured, in nodes across many servers
Engineer in EngineeringComputer Software Company, 51-200 employees
- 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.
Likelihood to Renew
Based on 8 answers
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
Based on 3 answers
I found it really useful during my academic projects. Data handling for large data sets was easy with Hadoop. It used to work really fast for bigger data sets. I found it reliable.
Based on 3 answers
Hadoop support is just average based on our experience. This is one area where it would be nice to see some improvement. Granted, we haven't had many issues with Hadoop that have required support.
Based on 2 answers
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
We considered using Relationship database with Oracle Database and Java applications to process our data but ended up with Hadoop despite it being almost new. However, it proved to be the correct solution, we just need a little time to get started with Hadoop and it allows it to save cost on license and EC2 cost as we configure DataNode to be on-demand or spot instance, it also provides high performance and easy to implement as Map-Reduce function is quite simple.
Return on Investment
- Hadoop was thought to be cheap, but it is actually a very expensive proposition.
- Support is required for Hadoop, so it is not free from a support perspective.
- The overall benefit of Hadoop is extensive scale out storage and processing, but it is difficult to tie it to ROI in a major corporation.
Executive in Professional ServicesInformation Services Company, 51-200 employees
Premium Consulting/Integration Services—
Entry-level set up fee?