Compare Apache Spark vs. JethroData

Apache Spark is ranked 1st in Hadoop with 7 reviews while JethroData is ranked 4th in BI on Hadoop. Apache Spark is rated 8.0, while JethroData is rated 0. The top reviewer of Apache Spark writes "Fast performance and has an easy initial setup". On the other hand, Apache Spark is most compared with Spring Boot, AWS Lambda and Azure Stream Analytics, whereas JethroData is most compared with AtScale, Apache Spark and Splice Machine.
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Apache Spark Logo
11,254 views|9,257 comparisons
JethroData Logo
1,590 views|1,302 comparisons
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Ranking
1st
out of 24 in Hadoop
Views
11,254
Comparisons
9,257
Reviews
7
Average Words per Review
207
Avg. Rating
8.0
4th
out of 8 in BI on Hadoop
Views
1,590
Comparisons
1,302
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 32% of the time.
Compared 12% of the time.
Compared 80% of the time.
Compared 7% of the time.
Compared 7% of the time.
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JethroData
Overview

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

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.
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Sample Customers
NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi SolutionsAvis, Tata Communications, Fiat Chrysler, BICS, Symphony Health, iBasis, Data Realty, Fortune 100 Bank, Large Big Box US Retailer
Top Industries
REVIEWERS
Financial Services Firm29%
Software R&D Company29%
Healthcare Company14%
Non Profit14%
VISITORS READING REVIEWS
Software R&D Company31%
Comms Service Provider13%
Financial Services Firm10%
Media Company8%
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Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: November 2019.
378,809 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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