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Apache Spark Review
Updated March 16, 2019

Apache Spark Review

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with Apache Spark

We used Apache Spark within our department as a Solution Architecture team. It helped make big data processing more efficient since the same framework can be used for batch and stream processing.
  • Customizable, it integrates with Jupyter notebooks which was really helpful for our team.
  • Easy to use and implement.
  • It allows us to quickly build microservices.
  • Release cycles can be faster.
  • Sometimes it kicked some of the users out due to inactivity.
  • Positive impact on analyzing big data.
  • Fast customer service saved our time.
  • Easy to use which means less time spent on training the team.
It is easy to learn, read and to maintain. It brings the best of the Ruby on Rails framework from Java that helps to create a web service so easily. Communication is one of the most distinctive features of Apache Spark compared to alternative products. You are able to communicate with your colleague in your team who also uses Spark while you are on the phone.
It is beneficial to use Apache Spark if:
  • You are working with big data, preprocessing data before machine learning
  • Building simple microservices and creating PoC. It makes it easier to create REST and simple web APIs.
  • If you need great customer service, Apache Spark would be a great choice since they provide it 24/7.