Compare AWS Compute Optimizer vs. Apache Spark

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Apache Spark Logo
10,189 views|8,201 comparisons
AWS Compute Optimizer Logo
76 views|26 comparisons
Top Review
Find out what your peers are saying about Apache, Amazon, Zadara and others in Compute Service. Updated: September 2021.
536,114 professionals have used our research since 2012.
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Pricing and Cost Advice
"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."

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Questions from the Community
Top Answer: I don't think using Apache Spark without Hadoop has any major drawbacks or issues. I have used Apache Spark quite successfully with AWS S3 on many projects which are batch based. Yes for very high… more »
Top Answer: The solution has been very stable.
Top Answer: We use the open-source version. It is free to use. However, you do need to have servers. We have three or four. they can be on-premises or in the cloud.
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Ranking
1st
out of 14 in Compute Service
Views
10,189
Comparisons
8,201
Reviews
11
Average Words per Review
472
Rating
8.6
13th
out of 14 in Compute Service
Views
76
Comparisons
26
Reviews
0
Average Words per Review
0
Rating
N/A
Comparisons
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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

AWS Compute Optimizer recommends optimal AWS Compute resources for your workloads to reduce costs and improve performance by using machine learning to analyze historical utilization metrics. Over-provisioning compute can lead to unnecessary infrastructure cost and under-provisioning compute can lead to poor application performance. Compute Optimizer helps you choose the optimal Amazon EC2 instance types, including those that are part of an Amazon EC2 Auto Scaling group, based on your utilization data.

By applying the knowledge drawn from Amazon’s own experience running diverse workloads in the cloud, Compute Optimizer identifies workload patterns and recommends optimal compute resources. Compute Optimizer analyzes the configuration and resource utilization of your workload to identify dozens of defining characteristics, for example, if a workload is CPU-intensive, or if it exhibits a daily pattern or if a workload accesses local storage frequently. The service processes these characteristics and identifies the hardware resource headroom required by the workload. Compute Optimizer infers how the workload would have performed on various hardware platforms (e.g. Amazon EC2 instances types) and offers recommendations.

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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 Solutions
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Top Industries
REVIEWERS
Financial Services Firm40%
Computer Software Company20%
Marketing Services Firm10%
Non Profit10%
VISITORS READING REVIEWS
Computer Software Company24%
Comms Service Provider19%
Financial Services Firm11%
Media Company9%
No Data Available
Company Size
REVIEWERS
Small Business38%
Midsize Enterprise21%
Large Enterprise41%
No Data Available
Find out what your peers are saying about Apache, Amazon, Zadara and others in Compute Service. Updated: September 2021.
536,114 professionals have used our research since 2012.

Apache Spark is ranked 1st in Compute Service with 11 reviews while AWS Compute Optimizer is ranked 13th in Compute Service. Apache Spark is rated 8.6, while AWS Compute Optimizer 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, Azure Stream Analytics, AWS Batch, AWS Lambda and SAP HANA, whereas AWS Compute Optimizer is most compared with .

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