What users are saying about
127 Ratings
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Score 8.7 out of 100
16 Ratings
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Score 8.2 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 InfoSphere DataStage

DataStage is well suited for any size of company that's looking to move, transform, clean data and easily create data-warehouses that would help to make data ready to be presented for decision making. Data Stage would easily integrate with companies that use IBM DB2 as their main RDBMS.A scenario where it less suited could be cost. I have noticed IBM tools tend to be a little more costly than average.
Herber Gonzalez | TrustRadius Reviewer

Feature Rating Comparison

Data Source Connection

Apache Spark
IBM InfoSphere DataStage
6.6
Connect to traditional data sources
Apache Spark
IBM InfoSphere DataStage
8.9
Connecto to Big Data and NoSQL
Apache Spark
IBM InfoSphere DataStage
4.3

Data Transformations

Apache Spark
IBM InfoSphere DataStage
8.9
Simple transformations
Apache Spark
IBM InfoSphere DataStage
9.3
Complex transformations
Apache Spark
IBM InfoSphere DataStage
8.4

Data Modeling

Apache Spark
IBM InfoSphere DataStage
6.8
Data model creation
Apache Spark
IBM InfoSphere DataStage
5.9
Metadata management
Apache Spark
IBM InfoSphere DataStage
6.2
Business rules and workflow
Apache Spark
IBM InfoSphere DataStage
8.3
Collaboration
Apache Spark
IBM InfoSphere DataStage
5.2
Testing and debugging
Apache Spark
IBM InfoSphere DataStage
7.1
feature 1
Apache Spark
IBM InfoSphere DataStage
8.0

Data Governance

Apache Spark
IBM InfoSphere DataStage
6.3
Integration with data quality tools
Apache Spark
IBM InfoSphere DataStage
7.3
Integration with MDM tools
Apache Spark
IBM InfoSphere DataStage
5.2

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 InfoSphere DataStage

  • Very reliable in handling data extraction, data transformation and loading
  • Flexibility in connecting to different type of databases, relational or non-relational
  • Great features such as parallel processing, hash handling, etc.
  • You can also take advantage of its FTP functions, and scheduling features if you need to.
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 InfoSphere DataStage

  • You must understand and know the algorithms, since the wrong use of them generates more time in processing.
  • Metadata. You need to develop with connectors, and taking all the Metadata from the menu, all the data that you complete manually, you can't track it.
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 InfoSphere DataStage

IBM InfoSphere DataStage 9.0
Based on 2 answers
Our development teams in the company can easily achieve and develop any ETL scripts that are needed to massage and move the data as needed. The company has also maintain this tool for a very long time making it automatic when it comes to ETL needs. We are currently trying to make DataStage our main and probably unique ETL tool
Herber Gonzalez | TrustRadius Reviewer

Performance

Apache Spark

No score
No answers yet
No answers on this topic

IBM InfoSphere DataStage

IBM InfoSphere DataStage 9.0
Based on 1 answer
It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records.It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
Anonymous | TrustRadius Reviewer

Support Rating

Apache Spark

Apache Spark 8.3
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 InfoSphere DataStage

IBM InfoSphere DataStage 5.6
Based on 4 answers
I believe that IBM generally has one of the worst and most complex assistance systems (physical and online) that exists.
Filippo Orlando | TrustRadius Reviewer

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 InfoSphere DataStage

DataStage offers better integration capabilities without the need to write code manually. It also has a native ETL engine whereas MSIS requires a SQL Server. It has better integration capabilities with data quality, data profiling and data governance tools. The main drawback of DataStage vs. MSIS is pricing.
Gonzalo Angeleri | 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 InfoSphere DataStage

  • Provides us an excellent ETL application
  • Made our data handling easy
  • Provide the business with high quality reports
Anonymous | TrustRadius Reviewer

Pricing Details

Apache Spark

General

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

IBM InfoSphere DataStage

General

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

Rating Summary

Likelihood to Recommend

Apache Spark
8.6
IBM InfoSphere DataStage
8.1

Usability

Apache Spark
8.7
IBM InfoSphere DataStage
9.0

Performance

Apache Spark
IBM InfoSphere DataStage
9.0

Support Rating

Apache Spark
8.3
IBM InfoSphere DataStage
5.6

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