Compare Amazon EMR vs. Spark SQL

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Amazon EMR Logo
2,514 views|2,091 comparisons
Spark SQL Logo
645 views|324 comparisons
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"The initial setup is pretty straightforward."

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"The stability was fine. It behaved as expected.""Overall the solution is excellent.""The speed of getting data.""The performance is one of the most important features. It has an API to process the data in a functional manner.""It is a stable solution."

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Cons
"The dashboard management could be better. Right now, it's lacking a bit."

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"In the next release, maybe the visualization of some command-line features could be added.""The solution needs to include graphing capabilities. Including financial charts would help improve everything overall.""Anything to improve the GUI would be helpful.""In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper.""Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users."

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Questions from the Community
Top Answer: The initial setup is pretty straightforward.
Top Answer: The price of the solution may be a bit more than other competitors, such as Microsoft.
Top Answer: The dashboard management could be better. Right now, it's lacking a bit. I'd like more of a remote connection between my computer and the solution. We have multi-factor authentication, and at one… more »
Top Answer: It is a stable solution.
Top Answer: Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't… more »
Top Answer: We use it to gather all the transaction data. We have Hadoop and Spark in our system, and we use some easy process flows for transport.
Ranking
7th
out of 22 in Hadoop
Views
2,514
Comparisons
2,091
Reviews
1
Average Words per Review
492
Rating
4.0
6th
out of 22 in Hadoop
Views
645
Comparisons
324
Reviews
5
Average Words per Review
309
Rating
6.6
Popular Comparisons
Also Known As
Amazon Elastic MapReduce
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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.
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Learn more about Amazon EMR
Learn more about Spark SQL
Sample Customers
Yelp
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, Hitachi Solutions
Top Industries
VISITORS READING REVIEWS
Computer Software Company26%
Media Company24%
Comms Service Provider13%
Insurance Company5%
VISITORS READING REVIEWS
Comms Service Provider32%
Computer Software Company23%
Financial Services Firm9%
Media Company8%
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: March 2021.
475,208 professionals have used our research since 2012.

Amazon EMR is ranked 7th in Hadoop with 1 review while Spark SQL is ranked 6th in Hadoop with 5 reviews. Amazon EMR is rated 4.0, while Spark SQL is rated 6.6. The top reviewer of Amazon EMR writes "Stable but could offer better dashboard management and workarounds for multi-factor authentication". 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 Cloudera Distribution for Hadoop, Hortonworks Data Platform, Apache Spark, HPE Ezmeral Data Fabric and Pentaho Data Integration, whereas Spark SQL is most compared with Apache Spark and IBM Db2 Big SQL.

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