Apache Pig vs. Kognitio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Pig
Score 8.4 out of 10
N/A
Apache Pig is a programming tool for creating MapReduce programs used in Hadoop.N/A
Kognitio
Score 9.1 out of 10
N/A
WX2 is the data and analytics focused data warehouse appliance solution from UK company Kognitio.N/A
Pricing
Apache PigKognitio
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Apache PigKognitio
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
Apache PigKognitio
Small Businesses

No answers on this topic

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Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 9.3 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 9.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache PigKognitio
Likelihood to Recommend
8.1
(9 ratings)
9.0
(2 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
6.0
(1 ratings)
-
(0 ratings)
User Testimonials
Apache PigKognitio
Likelihood to Recommend
Apache
Apache Pig is best suited for ETL-based data processes. It is good in performance in handling and analyzing a large amount of data. it gives faster results than any other similar tool. It is easy to implement and any user with some initial training or some prior SQL knowledge can work on it. Apache Pig is proud to have a large community base globally.
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Kognitio
What you have are different strategies for data encoding, which makes the process quite flexible, it is perfectly done so that a joint and collaborative work can be carried out, this information analyzed in large quantities, is extremely vital for the company, by giving it the correct and timely reading
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Pros
Apache
  • Its performance, ease of use, and simplicity in learning and deployment.
  • Using this tool, we can quickly analyze large amounts of data.
  • It's adequate for map-reducing large datasets and fully abstracted MapReduce.
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Kognitio
  • Ultra fast query results.
  • IN Memory Database.
  • Easy integration to reporting services.
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Cons
Apache
  • UDFS Python errors are not interpretable. Developer struggles for a very very long time if he/she gets these errors.
  • Being in early stage, it still has a small community for help in related matters.
  • It needs a lot of improvements yet. Only recently they added datetime module for time series, which is a very basic requirement.
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Kognitio
  • Problems Could Be Encountered is particularly pronounced in more complex analyses.
  • Categorical variables are often not precise enough
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Usability
Apache
It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
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Kognitio
No answers on this topic
Support Rating
Apache
The documentation is adequate. I'm not sure how large of an external community there is for support.
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Kognitio
No answers on this topic
Alternatives Considered
Apache
Apache Pig might help to start things faster at first and it was one of the best tool years back but it lacks important features that are needed in the data engineering world right now. Pig also has a steeper learning curve since it uses a proprietary language compared to Spark which can be coded with Python, Java.
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Kognitio
We selected Kognitio because of the legacy systems that are still running. Also, we have legacy systems in place that are fit for Kognitio. End-user has good feedback on our side when we started implementing this solution. Current servers are compatible with Kognitio in place.
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Return on Investment
Apache
  • Higher learning curve than other similar technologies so on-boarding new engineers or change ownership of Apache Pig code tends to be a bit of a headache
  • Once the language is learned and understood it can be relatively straightforward to write simple Pig scripts so development can go relatively quickly with a skilled team
  • As distributed technologies grow and improve, overall Apache Pig feels left in the dust and is more legacy code to support than something to actively develop with.
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Kognitio
  • The implementation of the formats to integrate the users we have and the program is also good.
  • I also improve the control of aspects related to the work environment
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