Compare Amazon EMR vs. Spark SQL
Amazon EMR is ranked 9th in Hadoop while Spark SQL is ranked 7th in Hadoop with 3 reviews. Amazon EMR is rated 0, while Spark SQL is rated 6.6. On the other hand, the top reviewer of Spark SQL writes "GUI could be improved. Useful for speedily processing big data". Amazon EMR is most compared with Hortonworks Data Platform, Cloudera Distribution for Hadoop and Apache Spark, whereas Spark SQL is most compared with Informatica Big Data Parser, Apache Spark and AtScale Adaptive Analytics (A3).
 Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: March 2020. 407,401 professionals have used our research since 2012. |
Quotes From Members
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 Use our free recommendation engine to learn which Hadoop solutions are best for your needs. 407,401 professionals have used our research since 2012. | |
Ranking  | |
Views 2,993 Comparisons 2,498 Reviews 0 Average Words per Review 0 Avg. Rating N/A | Views 627 Comparisons 492 Reviews 3 Average Words per Review 344 Avg. Rating 6.7 |
Top Comparisons | |
 Compared 29% of the time. Compared 28% of the time.  Compared 21% of the time. |  Compared 27% of the time. Compared 22% of the time.  Compared 19% of the time. |
Also Known As | |
| Amazon Elastic MapReduce | |
Learn | |
| Amazon | Apache |
Overview | |
| Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances. | Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed. There are several ways to interact with Spark SQL including SQL and the Dataset API. When computing a result the same execution engine is used, independent of which API/language you are using to express the computation. This unification means that developers can easily switch back and forth between different APIs based on which provides the most natural way to express a given transformation. |
Offer | |
Learn more about Amazon EMR | Learn more about Spark SQL |
Sample Customers | |
| Yelp | Information Not Available |
Top Industries | |
Software R&D Company26% Media Company22% Comms Service Provider9% Insurance Company9% | No Data Available |
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: March 2020.
407,401 professionals have used our research since 2012.
See also Amazon EMR Reviews, Spark SQL Reviews, and our list of Best Hadoop Companies.
We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post
reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference
with LinkedIn, and personal follow-up with the reviewer when necessary.