--- title: Apache Pig Reviews meta\_title: 'Apache Pig Reviews 2026: Details, Pricing, & Features | G2' meta\_description: Filter 21 reviews by the users' company size, role or industry to find out how Apache Pig works for a business like yours. aggregate\_rating: rating\_value: 3.9 review\_count: 21 scale: '5' date\_modified: '2026-08-09' parent\_category: name: Big Data url: https://www.g2.com/categories/big-data ---

# Apache Pig Reviews & Product Details

Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

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## User Insights

Average based on 21 real user reviews.

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 ![Prashant V.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Prashant V.")
PV

Prashant V.

Enterprise (\> 1000 emp.)

3/20/2020

"Apache Pig makes it easy to create efficient data pipelines"

4.5/5

What do you like best about Apache Pig?

Apache Pig and its query language (Pig Latin) allowed us to create data pipelines with ease. The language is designed to reflect the way data pipelines are designed, so it discards extraneous data, supports user defined functions (UDFs) , and offers a lot of control over the data flow. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

Pig being a greedy language, will not evaluate data until it's actually needed. So errors are not visible unless you actually try to dump/print the data. There is no "debug" functionality to run the code in a dry-run mode. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

Unless you already have implementations of Pig in the company that you are building on top of, you might be better off with other newer technologies with more Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

I have used Pig for data piplining and aggregation. The flow of the language reflects the flow of the data and so it is intuitive to understand what the data transformation is doing. However it hasn't kept up with the latest advances in technologies. If you were choosing a language, you would be better off with either Hive or Spark. Pig also has a steeper learning curve since it uses a proprietary language (Pig Latin). Review collected by and hosted on G2.com.

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8/28/2020
Validated ReviewerIncentivizedSource: G2 invite

PK

Prashanth K.

Big Data Engineer

Enterprise (\> 1000 emp.)

4/18/2020

"Apache Pig has saved my life from forever coding!"

4.5/5

What do you like best about Apache Pig?

What I like best about Apache Pig how efficiently we can write any of our complex map reduce or spark jobs without having much deep knowledge of Java, Python, Groovy. Also, its easy to control the execution of job with the help of pig. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

What I dislike about Apache Pig is its error debugging consume most of its development time as it can be some times immature/unstable. Also the support community is very much less when compared to that of hadoop mapreduce or spark issues. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

For all of you who are facing writing complex mapreduce or spark jobs, you should definitely try pig Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

One of the problem which I was able to solve was, I was able to reduce latency using pig which was earlier observed while running spark jobs mainly due to optimization offered by Apache pig. Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

 ![Subhadipto P.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Subhadipto P.")
SP

Subhadipto P.

Engineer II

Enterprise (\> 1000 emp.)

7/31/2018

"Useful for map reducing huge dataset - application in transportation engineering for probe data"

4.5/5

What do you like best about Apache Pig?

It can handle some of the simple mathematical operations, along with reducing the data. Aggregating the data is extremely useful. Running DateTime functionalities in apache pig is really a useful feature for faster and quicker results. Pig works on datasets of around 150 to 180 GB per month and reduces them efficiently within say 10 to 12 minutes. I would definitely recommend Apache pig to any basic coding person in the field of transportation engineering to start using Apache pig, especially when you need to handle huge dataset. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

It cannot perform sequential operations, like taking consecutive lines and then comparing them. However, the workaround is to rank the segments, merge them and then perform the task. The main drawback still lies in the fact that it cannot be used to perform loops and nested loops across any variable(s). Hive might be a better choice in certain cases for that reason. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

Reducing huge volume of data Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Reducing speed data provided by INRIX to a monthly or a yearly aggregate. Pig is also utilized to calculate various existing traffic signals performances which were otherwise calculated using various small scale measures.

The main benefit of using pig on such operations is that any city agency can prepare the codes for once and run it throughout the city, or even they can extend it to a statewide level which will make it very efficient, quicker, and more reliable than the traditional way of handling them using SQL database Review collected by and hosted on G2.com.

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3/5/2020
Validated ReviewerIncentivizedSource: G2 invite

 ![Verified User in Computer Software](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Computer Software")
UC

Verified User in Computer Software

Enterprise (\> 1000 emp.)

1/18/2019

"Apache Pig "

4.5/5

What do you like best about Apache Pig?

Less number of instructions does big tasks of collecting, loading, consolidating the data. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

Not enough tools to debug

Incorrect/misleading exceptions Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Report generation

Data Analysis

Alert setup based on threshold

Triaging of the production issues. Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

 ![Verified User in Computer Software](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Computer Software")
UC

Verified User in Computer Software

Enterprise (\> 1000 emp.)

9/17/2017

"Powerful data analytics"

4.5/5

What do you like best about Apache Pig?

- SQL like syntax

- powerful and feature-rich Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

- Much more difficult to use than Hive

- takes a while to get used to and learn as compared with Hive Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Data insights for programmatic advertising Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

 ![kevin r.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "kevin r.")
KR

kevin r.

A/R Analyst - Write-offs

Internet

Enterprise (\> 1000 emp.)

3/10/2017

"Apache Pig"

5/5

What do you like best about Apache Pig?

The ecosystem and the way it works. Being able to implement and integrate what you currently use. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

I think getting started is a bit patchy but once you're familiar and used to it, it can be very helpful. Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Being able to utilize data efficiently regarding analytics. Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

 ![Verified User in Higher Education](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Higher Education")
UH

Verified User in Higher Education

Enterprise (\> 1000 emp.)

5/26/2016

"A very good big data solution for querying"

5/5

What do you like best about Apache Pig?

1. SQL like syntax.

2. Ease of use.

3. Short learning curve

4. Ease of maintenance

5. Decrease in development time. This is the biggest advantage especially considering vanilla map-reduce jobs' complexity, time-spent and maintenance of the programs. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

1. Slow for larger queries

2. Errors need to be better

3. Support is less

4. Source and Sink need to be present

5. Especially the errors that Pig produces due to UDFS(Python) are not helpful at all. When something goes wrong, it just gives exec error in udf even if problem is related to syntax or type error, let alone a logical one. This is a big one. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

You have UDFs which you want to parallellize and utilize for large amounts of data, then you are in luck. Use Pig as a base pipeline where it does the hard work and you just apply your UDF in the step that you want.

Lazy evaluation: unless you do not produce an output file or does not output any message, it does not get evaluated. This has an advantage in the logical plan, it could optimize the program beginning to end and optimizer could produce an efficient plan to execute.

Enjoys everything that Hadoop offers, parallelization, fault-tolerancy with many relational database features.

If you want to do apply some statistics to your dataset. Functional programming paradigm fits quite naturally to pipeline processes, so I expect it to be quite successful. Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

Data Analysis for the raw data we have. Initial data exploration has been useful with pig. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerSource: Organic

 ![Gökhan E.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Gökhan E.")
GE

Gökhan E.

Technology Consultant

Small-Business (50 or fewer emp.)

3/7/2016

"Big data? No problem with the operations!"

5/5

What do you like best about Apache Pig?

I have used apache pig on my part time job which handles big data and apache pig scripts helped me a lot. I have created custom functions and it makes easier to handle complex and huge tasks and makes easier to maintain after configuration. Also the system optimization of pig script jobs helped me to focuse on semantics and so. The default mode i mean the map reduce mode is very efficient. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

Sometimes i feel that our data is not that big in order to be handled with pig script. Its documentation makes me sweat and takes a lot of time to get used to. Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

I was using it in Ad platform and our servers were getting too much requests and datas. While targeting this data pig scripts helped me a lot. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

 ![Verified User in Internet](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Internet")
AI

Verified User in Internet

Small-Business (50 or fewer emp.)

3/17/2016

"Analyzing large data can be so easy with this tool!"

4.5/5

What do you like best about Apache Pig?

Pig is a great high level scripting language for operating with big datasets that work under the Apache's open-source project Hadoop. This software allow you to transforming and optimizes the data operations into MapReduce, something that can be challenging with others platforms.

I recomment this tool to my clients that need to manage a big list of users that will load a considerable amount of data daily. This can help you to clean, search and declares independent execution plans easily.

You can compare this tool with sql programming but the way this tool use UDF help you with ease call the functions directly with Java, Js, Python and of course the big Ruby. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

At the beginning was a bit difficult to get used to working under his pig latin language, however there is very good documentation online that allow you to manage your process.

Apache Pig it got many competitors so they will need to optimize the system because sometimes the scripts won't get you the ideal results. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

Learn Pig Latin and be ready to have an easy day of work Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

My clients used normally to big process with data sets that will contain specially json objects they will be available to solve very convoluted data sets. Review collected by and hosted on G2.com.

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Validated ReviewerSource: Organic

 ![Verified User in Information Technology and Services](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Information Technology and Services")
UI

Verified User in Information Technology and Services

Enterprise (\> 1000 emp.)

5/13/2014

"Awesome! Love this tool. "

5/5

What do you like best about Apache Pig?

Once you get through the ideas and concepts that this software set can do you will love it to. Its extremely procedural which really reminds me of sql programming. It is extremely powerful, can connect to Hbase and of course Hive. Review collected by and hosted on G2.com.

What do you dislike about Apache Pig?

Optimizing. This can be difficult and be considered "artsy". This is because pig creates map reduce jobs that run on hadoop. So if your cluster isn't totally optimized, just optimizing this scripts won't get you the best results. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Pig:

If you are looking for a tool that is more geared towards developers and not novice users than pig is your tool. It is free and lots of documentation online. Review collected by and hosted on G2.com.

What problems is Apache Pig solving and how is that benefiting you?

ELT. We use pig to process our disparate data sets, containing json objects and "normalized" data to create data warehouse structures in hive. We have realized that we are able to solve complex problems (joining for example) without having to write custom map reduce jobs. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

##### Pricing

Pricing details for this product isn’t currently available. Visit the vendor’s website to learn more.

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