Compare Apache NiFi vs. Apache Spark

Apache NiFi is ranked 2nd in Compute Service with 1 review while Apache Spark is ranked 1st in Compute Service with 11 reviews. Apache NiFi is rated 8.0, while Apache Spark is rated 8.0. The top reviewer of Apache NiFi writes "Open source solution that allows you to collect data with ease". On the other hand, the top reviewer of Apache Spark writes "Good Streaming features enable to enter data and analysis within Spark Stream". Apache NiFi is most compared with AWS Lambda, Google Cloud Dataflow and Azure Stream Analytics, whereas Apache Spark is most compared with Spring Boot, Azure Stream Analytics and AWS Lambda.
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Apache NiFi Logo
7,072 views|5,042 comparisons
Apache Spark Logo
10,923 views|9,163 comparisons
Most Helpful Review
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
The most valuable features of this solution are ease of use and implementation.

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The processing time is very much improved over the data warehouse solution that we were using.The main feature that we find valuable is that it is very fast.The features we find most valuable are the machine learning, data learning, and Spark Analytics.I feel the streaming is its best feature.The solution is very stable.The most valuable feature of this solution is its capacity for processing large amounts of data.I found the solution stable. We haven't had any problems with it.The scalability has been the most valuable aspect of the solution.

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Cons
There should be a better way to integrate a development environment with local tools.

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I would like to see integration with data science platforms to optimize the processing capability for these tasks.We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time.We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data.When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources.The solution needs to optimize shuffling between workers.When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data.It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster.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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Pricing and Cost Advice
It's an open-source solution.

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Ranking
2nd
out of 10 in Compute Service
Views
7,072
Comparisons
5,042
Reviews
1
Average Words per Review
827
Avg. Rating
8.0
1st
out of 10 in Compute Service
Views
10,923
Comparisons
9,163
Reviews
10
Average Words per Review
309
Avg. Rating
8.0
Top Comparisons
Compared 27% of the time.
Compared 18% of the time.
Compared 35% of the time.
Compared 10% of the time.
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Apache
Apache
Overview
Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

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Sample Customers
Information Not Available
NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
Top Industries
VISITORS READING REVIEWS
Software R&D Company33%
Insurance Company12%
Comms Service Provider11%
Media Company7%
REVIEWERS
Financial Services Firm29%
Software R&D Company29%
Non Profit14%
Marketing Services Firm14%
VISITORS READING REVIEWS
Software R&D Company32%
Comms Service Provider12%
Media Company10%
Financial Services Firm9%
Find out what your peers are saying about AWS Lambda vs. Apache Spark and other solutions. Updated: January 2020.
397,983 professionals have used our research since 2012.
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