What users are saying about

Apache Spark

99 Ratings
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Score 8.6 out of 101

Microsoft Azure HDInsight

24 Ratings
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Score 7.5 out of 101

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Likelihood to Recommend

Apache Spark

Apache Spark has rich APIs for regular data transformations or for ML workloads or for graph workloads, whereas other systems may not such a wide range of support. Choose it when you need to perform data transformations for big data as offline jobs, whereas use MongoDB-like distributed database systems for more realtime queries.
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Microsoft Azure HDInsight

For my purposes it is well suited, being marketing and advertising.
Kristin Page profile photo

Pros

  • Ease of use, the Spark API allows for minimal boilerplate and can be written in a variety of languages including Python, Scala, and Java.
  • Performance, for most applications we have found that jobs are more performant running via Spark than other distributed processing technologies like Map-Reduce, Hive, and Pig.
  • Flexibility, the frameworks comes with support for streaming, batch processing, sql queries, machine learning, etc. It can be used in a variety of applications without needing to integrate a lot of other distributed processing technologies.
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  • Shows live changes in analytics. Shows you how social media is working for us. Since we promote weekly events this is something that we really need to pay attention to.
  • Azure in itself is very user-friendly, HDInsight is a great addition. For our purposes, we definitely also utilized the power query to translate data to Excel.
Kristin Page profile photo

Cons

  • Resource heavy, jobs, in general, can be very memory intensive and you will want the nodes in your cluster to reflect that.
  • Debugging, it has gotten better with every release but sometimes it can be difficult to debug an error due to ambiguous or misleading exceptions and stack traces.
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  • The only problem I have come across is when loading large volumes of data I sometimes get an error message, I assume this means something is corrupt from within. I would love a way for this to be resolved without having to start over.
Kristin Page profile photo

Alternatives Considered

Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.
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At this time I have not used any other similar products... I am open to it but Azure HDInsight and its components really work well for our organization.
Kristin Page profile photo

Return on Investment

  • It has had a very positive impact, as it helps reduce the data processing time and thus helps us achieve our goals much faster.
  • Being easy to use, it allows us to adapt to the tool much faster than with others, which in turn allows us to access various data sources such as Hadoop, Apache Mesos, Kubernetes, independently or in the cloud. This makes it very useful.
  • It was very easy for me to use Apache Spark and learn it since I come from a background of Java and SQL, and it shares those basic principles and uses a very similar logic.
Carla Borges profile photo
  • The positive impact is high for our overall business objective; which is to advertise our events, sales, and new merchandise. ROI cannot be compared.
Kristin Page profile photo

Pricing Details

Apache Spark

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Microsoft Azure HDInsight

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details