Apache Pig

Apache Pig

22 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting 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

Pricing

Apache Pig

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Apache Pig
Free Trial
No
Free/Freemium Version
No
Premium Consulting/Integration Services
No

Entry-level Setup Fee

No setup fee

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Community Pulse
	Apache Pig
Considered Both Products	Apache Pig Sourov K Chowdhury Database Software Engineer Chose Apache Pig It takes me less time to write a Pig script than get a Spark program running for batch ETL workloads. Compared to Spark, Pig has a steeper learning curve because it employs a proprietary programming language. In one script and one fine, it can handle both Map Reduce and Hadoop. … Incentivized Helpful? Verified User C-Level Executive Chose Apache Pig It can accommodate Map Reduce in a single script and a single fine. IT has very much documentation present for easy learning. SQL like queries makes it easy to understand Helpful? Verified User Engineer Chose Apache Pig 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 … Incentivized Helpful? Jordan Moore Software Consultant Chose Apache Pig Pig is more focused on scripting in its own PigLatin language rather than integrate into another language like Java/Scala/Python/SQL. However, for batch ETL workloads, I find that I can write a Pig script quicker than setting up and deploying a Spark program, for example. Incentivized Helpful? Subhadipto Poddar Research Assistant Chose Apache Pig Apache Pig is picked up quickly and can be implemented with very little coding skills. Also the other languages require exact matching of versions during installations which made them somewhat less user-friendly. Also most of the tasks that are done in map reduce can be done … Incentivized Helpful? Kartik Chavan Data Analyst Chose Apache Pig I use both Apache Pig and its alternatives like Apache Spark & Apache Hive. Apache Pig was one of the best options in Big Data's initial stages. But now alternatives have taken over the market, rendering Apache Pig behind in the competition. But it is still a better alternative … Incentivized Helpful? Verified User Engineer Chose Apache Pig Early on Apache Pig was a great tool for easily writing distributed processing applications without needing to write a complete Java MapReduce job from scratch, but as time as moved on there now better alternatives to get results faster for both ad-hoc analysis and for … Incentivized Helpful? Verified User Team Lead Chose Apache Pig - Provided better ways for optimized hadoop jobs than Hive but not anymore. - Spark DSL is much more advanced and compute times are significantly less. Incentivized Helpful?
Top Pros	Pro Easy to learn Pro Big data Pro Large datasets
Top Cons	Minus Hard to navigate Minus Training materials Minus Not support

Best Alternatives
	Apache Pig
Small Businesses	No answers on this topic
Medium-sized Companies	Cloudera Manager Score 9.7 out of 10
Enterprises	IBM Analytics Engine Score 8.8 out of 10
All Alternatives	View all alternatives

User Ratings
	Apache Pig
Likelihood to Recommend	8.1 (9 ratings)
Usability	10.0 (1 ratings)
Support Rating	6.0 (1 ratings)

User Testimonials
	Apache Pig
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. Incentivized Verified User Anonymous Read full review
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. Incentivized Sourov K Chowdhury Database Software Engineer Read full review
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. Incentivized Kartik Chavan Data Analyst Read full review
Usability	Apache It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used. Incentivized Subhadipto Poddar Research Assistant Read full review
Support Rating	Apache The documentation is adequate. I'm not sure how large of an external community there is for support. Incentivized Jordan Moore Software Consultant Read full review
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. Incentivized Verified User Anonymous Read full review
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. Incentivized Verified User Anonymous Read full review
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