Compare JethroData vs. Spark SQL

JethroData is ranked 4th in BI on Hadoop while Spark SQL is ranked 7th in Hadoop with 1 review. JethroData is rated 0, while Spark SQL is rated 8.0. On the other hand, the top reviewer of Spark SQL writes "A good stable and scalable solution for processing big data". JethroData is most compared with AtScale, Apache Spark and Splice Machine, whereas Spark SQL is most compared with Apache Spark, Informatica Big Data Parser and AtScale.
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JethroData Logo
1,675 views|1,370 comparisons
Spark SQL Logo
645 views|511 comparisons
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Ranking
4th
out of 8 in BI on Hadoop
Views
1,675
Comparisons
1,370
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
7th
out of 24 in Hadoop
Views
645
Comparisons
511
Reviews
1
Average Words per Review
226
Avg. Rating
8.0
Top Comparisons
Compared 77% of the time.
Compared 7% of the time.
Compared 7% of the time.
Compared 28% of the time.
Compared 17% of the time.
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JethroData
Apache
Overview
Jethro is a performance acceleration engine that delivers interactive Business Intelligence (BI) on Big Data at Hadoop costs. Jethro accelerates Big Data performance with Tableau, Qlik, MicroStrategy as well as in-house BI applications. - Interactive Performance: Jethro delivers response in seconds on 10s of billions of rows—on any SQL query - High Concurrency: 1,000s of concurrent users can access the same data without impacting performance. - No Data Engineering: Jethro automatically handles all of the costly, ineffective and endless data engineering Jethro is data source agnostic and is compatible with any Hadoop distribution, AWS, EFS, Azure and almost any other data source.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 Spark SQL
Sample Customers
Avis, Tata Communications, Fiat Chrysler, BICS, Symphony Health, iBasis, Data Realty, Fortune 100 Bank, Large Big Box US Retailer
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