Apache Pig vs. Apache Spark

Apache Pig

22 Reviews and Ratings

Apache Spark

161 Reviews and Ratings

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Apache Pig	Score8.4 out of 10	N/A	Apache Pig is a programming tool for creating MapReduce programs used in Hadoop.	$0
Apache Spark	Score9.2 out of 10	N/A	Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.	N/A

Pricing

Apache Pig

Apache Spark

No answers on this topic

No answers on this topic

Pricing Offerings
Apache Pig	Apache Spark
Free Trial
No	No
Free/Freemium Version
Yes	No
Premium Consulting/Integration Services
No	No

No setup fee

No setup fee

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Community Pulse
Key User Insights
	Apache Pig	Apache Spark
Considered Both Products	Apache Kartik Chavan Data Analyst in Information Technology at The University of Texas at Arlington (Electrical/Electronic Manufacturing, 1001-5000 employees) 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? Sourov K Chowdhury Database Software Engineer in Product Management at Best Web Design Ltd. (Information Technology & Services, 11-50 employees) 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 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 in Information Technology at Avalon Consulting (Information Technology and Services, 51-200 employees) 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? Verified User 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 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?	Apache Kamesh Emani Software Developer Intern in Information Technology at Louisiana Tech University (Higher Education, 1001-5000 employees) Chose Apache Spark Apache Pig and Apache Hive provide most of the things spark provide but apache spark has more features like actions and transformations which are easy to code. Spark uses optimization technique as we can select driver program and manipulate DAG (Directed Acyclic Graph) Python … Incentivized Helpful? Jordan Moore Staff Consultant in Information Technology at Avalon Consulting, LLC (Information Technology and Services, 51-200 employees) Chose Apache Spark Spark has primarily replaced my use of writing pure Hadoop MapReduce or Apache Pig jobs for processing data. I like the fact that I can alternate between the main programming languages that I know - Java and Python - and use those to learn the Scala API. Spark also can be … Incentivized Helpful? Nitin Pasumarthy Software Engineer in Engineering at LinkedIn (Internet, 5001-10,000 employees) Chose Apache Spark All the above systems work quite well on big data transformations whereas Spark really shines with its bigger API support and its ability to read from and write to multiple data sources. Using Spark one can easily switch between declarative versus imperative versus functional … Incentivized Helpful? Kartik Chavan Data Analyst in Information Technology at The University of Texas at Arlington (Electrical/Electronic Manufacturing, 1001-5000 employees) Chose Apache Spark Even with Python, MapReduce is lengthy coding. Combination of Python with Apache Spark will not only shorten the code, but it will effectively increase the speed of algorithms. Occasionally, I use MapReduce, but Apache Spark will replace MapReduce very soon. It has many … Incentivized Helpful? Verified User Chose 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 … Incentivized Helpful?
	Would buy again
	No answers on this topic	No answers on this topic
	Delivers good value for the price
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	Happy with the feature set
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	Lived up to sales and marketing promises
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	Implementation went as expected
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User Ratings
	Apache Pig	Apache Spark
Likelihood to Recommend	8.2 (9 ratings)	9.0 (24 ratings)
Likelihood to Renew	- (0 ratings)	10.0 (1 ratings)
Usability	10.0 (1 ratings)	8.0 (4 ratings)
Support Rating	6.0 (1 ratings)	8.7 (4 ratings)