Compare Apache Flink vs. Azure Stream Analytics

Apache Flink is ranked 7th in Streaming Analytics while Azure Stream Analytics is ranked 1st in Streaming Analytics with 1 review. Apache Flink is rated 0, while Azure Stream Analytics is rated 8.0. On the other hand, the top reviewer of Azure Stream Analytics writes "Helps us focus on critical security issues, among our multiple systems". Apache Flink is most compared with Amazon Kinesis, Azure Stream Analytics and Spring Cloud Data Flow, whereas Azure Stream Analytics is most compared with Apache Spark, Apache NiFi and Apache Flink.
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Apache Flink Logo
1,062 views|1,005 comparisons
Azure Stream Analytics Logo
3,327 views|2,828 comparisons
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Ranking
7th
out of 25 in Streaming Analytics
Views
1,062
Comparisons
1,005
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
1st
out of 25 in Streaming Analytics
Views
3,327
Comparisons
2,828
Reviews
1
Average Words per Review
710
Avg. Rating
8.0
Top Comparisons
Compared 38% of the time.
Also Known As
FlinkASA
Learn
Apache
Microsoft
Overview

Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale.

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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Learn more about Apache Flink
Learn more about Azure Stream Analytics
Sample Customers
Information Not Available
Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
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.
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