What users are saying about
127 Ratings
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Score 8.7 out of 100
18 Ratings
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Score 5.9 out of 100

Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
Thomas Young | TrustRadius Reviewer

IBM Netezza Performance Server

Large companies 500+ with multiple analysts who needs to work simultaneously in the database.
Anonymous | TrustRadius Reviewer

Pros

Apache Spark

  • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
  • Faster in execution times compare to Hadoop and PIG Latin
  • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
  • Interoperability between SQL and Scala / Python style of munging data
Nitin Pasumarthy | TrustRadius Reviewer

IBM Netezza Performance Server

  • Fast Queries
  • Handles Extra Large Data Sets
  • Easy to Manage
Anonymous | TrustRadius Reviewer

Cons

Apache Spark

  • Memory management. Very weak on that.
  • PySpark not as robust as scala with spark.
  • spark master HA is needed. Not as HA as it should be.
  • Locality should not be a necessity, but does help improvement. But would prefer no locality
Anson Abraham | TrustRadius Reviewer

IBM Netezza Performance Server

  • Cannot use functions such as pivot, which is in MS SQL Server
  • Objects such as tables do not pop up automatically in the editor, users needs to navigate themselves to know the object names
Anonymous | TrustRadius Reviewer

Usability

Apache Spark

Apache Spark 8.7
Based on 3 answers
Apache integrates with multiple big data frameworks. It does not exert too much load on the disks. Moreover, it is easy to program and use. It reduces the headache of using different applications separately through its high-level APIs. Big data processing has never been as easy as it is with Apache Spark.
Partha Protim Pegu | TrustRadius Reviewer

IBM Netezza Performance Server

No score
No answers yet
No answers on this topic

Support Rating

Apache Spark

Apache Spark 8.2
Based on 6 answers
1. It integrates very well with scala or python.2. It's very easy to understand SQL interoperability.3. Apache is way faster than the other competitive technologies.4. The support from the Apache community is very huge for Spark.5. Execution times are faster as compared to others.6. There are a large number of forums available for Apache Spark.7. The code availability for Apache Spark is simpler and easy to gain access to.8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Yogesh Mhasde | TrustRadius Reviewer

IBM Netezza Performance Server

No score
No answers yet
No answers on this topic

Alternatives Considered

Apache Spark

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.
Anonymous | TrustRadius Reviewer

IBM Netezza Performance Server

IBM Netezza Data Warehouse Appliances is well suited for use by a larger organization wanting to solve the business problems related to the collection, transformation, and dissemination of our company's business process information. These means the small data sets or data warehouse less than 1TB are best done with a different tool like SQL Server.
Anonymous | TrustRadius Reviewer

Return on Investment

Apache Spark

  • 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 | TrustRadius Reviewer

IBM Netezza Performance Server

  • It allows us to work together simultaneously in the database to query our custom results.
  • It requires users to know the object name as it does not pop up in their text editor. Thus, users take more time in writing queries.
Anonymous | TrustRadius Reviewer

Pricing Details

Apache Spark

General

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

IBM Netezza Performance Server

General

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

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