Compare Apache Spark vs. Azure Stream Analytics

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Apache Spark Logo
11,227 views|9,365 comparisons
Azure Stream Analytics Logo
4,738 views|4,127 comparisons
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Questions from the Community
Top Answer: I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
Top Answer: I love every core functionality of Apache Spark Initially they have only provided RDD basic interface to process the data across distributed cluster. Then it evolved to dataframe and dataset interface… more »
Top Answer: Apache spark is available in cloud services like AWS cloud, Azure. We have to use the specific service for our use case. For example we can use AWS Glue which runs spark for ETL process, AWS EMR… more »
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Ranking
1st
out of 26 in Hadoop
Views
11,227
Comparisons
9,365
Reviews
11
Average Words per Review
353
Avg. Rating
8.2
3rd
out of 32 in Streaming Analytics
Views
4,738
Comparisons
4,127
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Popular Comparisons
Compared 33% of the time.
Compared 7% of the time.
Compared 7% of the time.
Compared 6% of the time.
Compared 5% of the time.
Compared 29% of the time.
Also Known As
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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

AzureStream Analytics is a fully managed event-processing engine that lets you set up real-time analytic computations on streaming data.The data can come from devices, sensors, web sites, social media feeds, applications, infrastructure systems, and more.
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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 SolutionsRockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
Top Industries
REVIEWERS
Financial Services Firm29%
Computer Software Company29%
Healthcare Company14%
Marketing Services Firm14%
VISITORS READING REVIEWS
Computer Software Company35%
Media Company14%
Comms Service Provider10%
University5%
VISITORS READING REVIEWS
Computer Software Company50%
Comms Service Provider9%
Media Company7%
Retailer5%
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: August 2020.
437,557 professionals have used our research since 2012.
Apache Spark is ranked 1st in Hadoop with 11 reviews while Azure Stream Analytics is ranked 3rd in Streaming Analytics. Apache Spark is rated 8.2, while Azure Stream Analytics is rated 0.0. The top reviewer of Apache Spark writes "Good Streaming features enable to enter data and analysis within Spark Stream". On the other hand, Apache Spark is most compared with Spring Boot, SAP HANA, AWS Batch, AWS Lambda and Apache NiFi, whereas Azure Stream Analytics is most compared with Databricks, Apache NiFi, Apache Flink, Apache Spark Streaming and Google Cloud Dataflow.

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