What users are saying about
24 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>Score 7.9 out of 100
Based on 24 reviews and ratings
145 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>Score 8.8 out of 100
Based on 145 reviews and ratings
Attribute Ratings
- Apache Pig is rated higher in 1 area: Usability
- Apache Spark is rated higher in 2 areas: Likelihood to Recommend, Support Rating
Likelihood to Recommend

7.4
Apache Pig
74%
8 Ratings

9.2
Apache Spark
92%
22 Ratings
Likelihood to Renew

Apache Pig
N/A
0 Ratings

10.0
Apache Spark
100%
1 Rating
Usability

10.0
Apache Pig
100%
1 Rating

9.4
Apache Spark
94%
2 Ratings
Support Rating

6.0
Apache Pig
60%
2 Ratings

8.7
Apache Spark
87%
6 Ratings
Likelihood to Recommend
Apache Pig
Apache Pig is a lightweight framework that is simple to learn and put into production. It converts MapReduce tasks into SQL-like queries. It also reduces the data and performs some simple mathematical functions. Combining data is incredibly beneficial. With Apache Pig's Data Time functions, we can get quicker results. It works on 150-180 GB monthly datasets and reduces them in a few minutes. However, it cannot perform sequential operations, such as comparing consecutive lines. And another flaw of this method is that it doesn't allow loops and nested loops to span more than one variable at a time. Then again, I'd say go for it!
Database Software Engineer
Best Web Design Ltd.Information Technology & Services, 11-50 employees
Apache Spark
The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
Owner, previous CEO
Econometric StudiosFinancial Services, 11-50 employees
Pros
Apache Pig
- Long logics in Java? Apache Pig is a good alternative.
- Has a lot of great features including table joins on many databases like DBMS, Hive, Spark-SQL etc.
- Faster & easy development compared to regular map-reduce jobs.
Data Analyst
The University of Texas at ArlingtonElectrical/Electronic Manufacturing, 1001-5000 employees
Apache Spark
- Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
- Faster in execution times compare to Hadoop and PIG Latin
- Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
- Interoperability between SQL and Scala / Python style of munging data
Software Engineer
LinkedInInternet, 5001-10,000 employees
Cons
Apache Pig
- General syntax for the FOREACH ... GENERATE feature is confusing for nested actions.
- The docs are hard to navigate, but it is made up for by reasonable examples.
- A version less than 1.0 doesn't instill confidence in the product that has been around for over half a decade (as of writing).
Software Consultant
Avalon ConsultingInformation Technology and Services, 51-200 employees
Apache Spark
- Memory management. Very weak on that.
- PySpark not as robust as scala with spark.
- spark master HA is needed. Not as HA as it should be.
- Locality should not be a necessity, but does help improvement. But would prefer no locality
Data Czar
Envisagenics, Inc.Marketing and Advertising, 51-200 employees
Pricing Details
Apache Pig
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Starting Price
—Apache Spark
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Starting Price
—Likelihood to Renew
Apache Pig
No score
No answers yet
No answers on this topic
Apache Spark
Apache Spark 10.0
Based on 1 answer
Capacity of computing data in cluster and fast speed.
Senior Software Developer (Consultant)
Morgan StanleyBanking, 10,001+ employees
Usability
Apache Pig
Apache Pig 10.0
Based on 1 answer
It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
Research Assistant
Iowa State UniversityHigher Education, 5001-10,000 employees
Apache Spark
Apache Spark 9.4
Based on 2 answers
The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.

Verified User
Engineer in Information Technology
Information Technology & Services Company, 11-50 employeesSupport Rating
Apache Pig
Apache Pig 6.0
Based on 2 answers
The documentation is adequate. I'm not sure how large of an external community there is for support.
Software Consultant
Avalon ConsultingInformation Technology and Services, 51-200 employees
Apache Spark
Apache Spark 8.7
Based on 6 answers
1. It integrates very well with scala or python.2. It's very easy to understand SQL interoperability.3. Apache is way faster than the other competitive technologies.4. The support from the Apache community is very huge for Spark.5. Execution times are faster as compared to others.6. There are a large number of forums available for Apache Spark.7. The code availability for Apache Spark is simpler and easy to gain access to.8. Many organizations use Apache Spark, so many solutions are available for existing applications.
Technical Manager
Rishabh Software Private LimitedInformation Technology & Services, 501-1000 employees
Alternatives Considered
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 which can be coded with Python, Java.

Verified User
Engineer in Engineering
Internet Company, 5001-10,000 employeesApache 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 getting the ability to write your application in the language of your choosing.

Verified User
Engineer in Engineering
Computer Software Company, 51-200 employeesReturn on Investment
Apache Pig
- 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.

Verified User
Engineer in Engineering
Computer Software Company, 51-200 employeesApache Spark
- Business leaders are able to take data driven decisions
- Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
- Business is able come up with new product ideas
Senior Data Engineer
A.P. Moller - MaerskLogistics & Supply Chain, 10,001+ employees