Compare Amazon MSK vs. Apache Spark Streaming

Amazon MSK is ranked 13th in Streaming Analytics while Apache Spark Streaming is ranked 10th in Streaming Analytics. Amazon MSK is rated 0, while Apache Spark Streaming is rated 0. On the other hand, Amazon MSK is most compared with Confluent and Amazon Kinesis, whereas Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics and Spring Cloud Data Flow.
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Amazon MSK Logo
Amazon MSK
547 views|523 comparisons
Apache Spark Streaming Logo
Apache Spark Streaming
1,551 views|1,488 comparisons
Ranking
13th
out of 31 in Streaming Analytics
Views
547
Comparisons
523
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
10th
out of 31 in Streaming Analytics
Views
1,551
Comparisons
1,488
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Confluent vs. Amazon MSK
Compared 66% of the time.
Amazon Kinesis vs. Amazon MSK
Compared 34% of the time.
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Also Known As
Amazon Managed Streaming for Apache KafkaSpark Streaming
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Overview

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.

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Learn more about Apache Spark Streaming
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Sample Customers
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Information Not Available
Top Industries
VISITORS READING REVIEWS
Media Company33%
Software R&D Company23%
Comms Service Provider12%
Retailer9%
VISITORS READING REVIEWS
Software R&D Company51%
Media Company11%
Retailer11%
Comms Service Provider6%

See also Amazon MSK Reviews, Apache Spark Streaming Reviews, and our list of Best Streaming Analytics Companies.

We monitor all Streaming Analytics 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.