Apache Spark Pros and Cons

Apache Spark Pros

Karthikeyan R
Principal Architect at a financial services firm with 1,001-5,000 employees
I found the solution stable. We haven't had any problems with it.
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reviewer1046250
Senior Consultant & Training at a tech services company with 51-200 employees
The most valuable feature of this solution is its capacity for processing large amounts of data.
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Snrsecengin567
Snr Security Engineer at a tech vendor with 201-500 employees
The scalability has been the most valuable aspect of the solution.
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Abhijit Nayak
Manager | Data Science Enthusiast | Management Consultant at a consultancy with 5,001-10,000 employees
With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware.
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reviewer894894
User
Features include machine learning, real time streaming, and data processing.
The fault tolerant feature is provided.
It provides a scalable machine learning library.
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Apache Spark Cons

Karthikeyan R
Principal Architect at a financial services firm with 1,001-5,000 employees
It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster.
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reviewer1046250
Senior Consultant & Training at a tech services company with 51-200 employees
When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data.
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Snrsecengin567
Snr Security Engineer at a tech vendor with 201-500 employees
The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive.
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Find out what your peers are saying about Apache, Informatica, Pivotal and others in Hadoop. Updated: November 2019.
379,605 professionals have used our research since 2012.
Abhijit Nayak
Manager | Data Science Enthusiast | Management Consultant at a consultancy with 5,001-10,000 employees
Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing.
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reviewer894894
User
It should support more programming languages.
Needs to provide an internal schedule to schedule spark jobs with monitoring capability.
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Find out what your peers are saying about Apache, Informatica, Pivotal and others in Hadoop. Updated: November 2019.
379,605 professionals have used our research since 2012.
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