Apache Pig vs. Azure HDInsight

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.

Incentivized

If you want to save costs and just pay for what you use, I highly recommend it. It will help you also to work with data for your reports and analytics. on the other hand I think it could be the subscription you have but high volume of data make it slow but not so much. anyway I think it's really good because it's from Microsoft which always is friendly to use it as all the suit they have.

Incentivized

• 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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• Data is presented without interfering others (IT or other dept).
• Data is managed properly and is available for retrievable any time.
• Legacy use of CD/DVD and Pendrive are not required.

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• 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.

Incentivized

• 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.

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It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.

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Azure HDInsight is usable on the top of Azure Data Lake and gives us the benefit of analyzing large scale data workload in Hadoop. Usability and support from Microsoft are outstanding.

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The documentation is adequate. I'm not sure how large of an external community there is for support.

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I highly recommend it.

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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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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.

Incentivized

• 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.

Incentivized

• Less implementation cost.
• No hosting services cost.
• Faster data retrieval.

Incentivized