Compare Amazon Kinesis vs. Apache Spark Streaming

Amazon Kinesis is ranked 8th in Streaming Analytics while Apache Spark Streaming is ranked 10th in Streaming Analytics. Amazon Kinesis is rated 0, while Apache Spark Streaming is rated 0. On the other hand, Amazon Kinesis is most compared with Apache Flink, Apache Spark Streaming and Google Cloud Dataflow, whereas Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics and Spring Cloud Data Flow.
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Amazon Kinesis Logo
1,624 views|1,565 comparisons
Apache Spark Streaming Logo
887 views|849 comparisons
Ranking
8th
out of 27 in Streaming Analytics
Views
1,624
Comparisons
1,565
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
10th
out of 27 in Streaming Analytics
Views
887
Comparisons
849
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 37% of the time.
Also Known As
Amazon AWS Kinesis, AWS Kinesis, KinesisSpark Streaming
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Amazon
Apache
Overview

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

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

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Learn more about Amazon Kinesis
Learn more about Apache Spark Streaming
Sample Customers
Zillow, Netflix, Sonos
Information Not Available
Top Industries
VISITORS READING REVIEWS
Software R&D Company38%
Media Company25%
Comms Service Provider8%
Retailer6%
No Data Available
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