Compare Spark SQL vs. Splice Machine

Spark SQL is ranked 7th in Hadoop with 1 review while Splice Machine is ranked 13th in Hadoop. Spark SQL is rated 8.0, while Splice Machine is rated 0. The top reviewer of Spark SQL writes "A good stable and scalable solution for processing big data". On the other hand, Spark SQL is most compared with Apache Spark, Informatica Big Data Parser and AtScale, whereas Splice Machine is most compared with JethroData, Cloudera Distribution for Hadoop and AtScale.
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Spark SQL Logo
645 views|511 comparisons
Splice Machine Logo
462 views|292 comparisons
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: September 2019.
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Ranking
7th
out of 24 in Hadoop
Views
645
Comparisons
511
Reviews
1
Average Words per Review
226
Avg. Rating
8.0
13th
out of 24 in Hadoop
Views
462
Comparisons
292
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 28% of the time.
Compared 17% of the time.
Compared 27% of the time.
Compared 15% of the time.
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Overview
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.Splice Machine is an application platform built to power predictive applications that manage operational processes, large-scale IoT infrastructures, analytical processing and machine learning. It is a Hybrid RDBMS that can be delivered as a cloud service, or used on premise through our Enterprise Edition or Community Edition.
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Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: September 2019.
371,639 professionals have used our research since 2012.
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.
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