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Apache Flink vs Azure Stream Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Apache Flink
Ranking in Streaming Analytics
6th
Average Rating
7.6
Reviews Sentiment
6.9
Number of Reviews
16
Ranking in other categories
No ranking in other categories
Azure Stream Analytics
Ranking in Streaming Analytics
3rd
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
26
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Apache Flink is 13.2%, up from 9.5% compared to the previous year. The mindshare of Azure Stream Analytics is 10.4%, down from 12.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Ilya Afanasyev - PeerSpot reviewer
A great solution with an intricate system and allows for batch data processing
We value this solution's intricate system because it comes with a state inside the mechanism and product. The system allows us to process batch data, stream to real-time and build pipelines. Additionally, we do not need to process data from the beginning when we pause, and we can continue from the same point where we stopped. It helps us save time as 95% of our pipelines will now be on Amazon, and we'll save money by saving time.
SantiagoCordero - PeerSpot reviewer
Native connectors and integration simplify tasks but portfolio complexity needs addressing
There are too many products in the Azure landscape, which sometimes leads to overlap between them. Microsoft continuously releases new products or solutions, which can be frustrating when determining the appropriate features from one solution over another. A cost comparison between products is also not straightforward. They should simplify their portfolio. The Microsoft licensing system is confusing and not easy to understand, and this is something they should address. In the future, I may stop using Stream Analytics and move to other solutions. I discussed Palantir earlier, which is something I want to explore in depth because it allows me to accomplish more efficiently compared to solely using Azure. Additionally, the vendors should make the solution more user-friendly, incorporating low-code and no-code features. This is something I wish to explore further.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The documentation is very good."
"Allows us to process batch data, stream to real-time and build pipelines."
"The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"Another feature is how Flink handles its radiuses. It has something called the checkpointing concept. You're dealing with billions and billions of requests, so your system is going to fail in large storage systems. Flink handles this by using the concept of checkpointing and savepointing, where they write the aggregated state into some separate storage. So in case of failure, you can basically recall from that state and come back."
"Apache Flink's best feature is its data streaming tool."
"The event processing function is the most useful or the most used function. The filter function and the mapping function are also very useful because we have a lot of data to transform. For example, we store a lot of information about a person, and when we want to retrieve this person's details, we need all the details. In the map function, we can actually map all persons based on their age group. That's why the mapping function is very useful. We can really get a lot of events, and then we keep on doing what we need to do."
"The setup was not too difficult."
"It is user-friendly and the reporting is good."
"The most valuable features are the IoT hub and the Blob storage."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"Provides deep integration with other Azure resources."
"It's scalable as a cloud product."
"The life cycle, report management and crash management features are great."
"The most valuable aspect is the SQL option that Azure Stream Analytics provides."
"I like the IoT part. We have mostly used Azure Stream Analytics services for it"
"It's easy to implement and maintain pipelines with minimal complexity."
 

Cons

"Apache Flink should improve its data capability and data migration."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"There are more libraries that are missing and also maybe more capabilities for machine learning."
"The solution could be more user-friendly."
"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."
"In a future release, they could improve on making the error descriptions more clear."
"There is room for improvement in the initial setup process."
"The machine learning library is not very flexible."
"Easier scalability and more detailed job monitoring features would be helpful."
"It is not complex, but it requires some development skills. When the data is sent from Azure Stream Analytics to Power BI, I don't have the access to modify the data. I can't customize or edit the data or do some queries. All queries need to be done in the Azure Stream Analytics."
"The collection and analysis of historical data could be better."
"The UI should be a little bit better from a usability perspective."
"There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting."
"The solution's interface could be simpler to understand for non-technical people."
"Its features for event imports and architecture could be enhanced."
"There are too many products in the Azure landscape, which sometimes leads to overlap between them."
 

Pricing and Cost Advice

"Apache Flink is open source so we pay no licensing for the use of the software."
"This is an open-source platform that can be used free of charge."
"It's an open source."
"The solution is open-source, which is free."
"It's an open-source solution."
"The product's price is at par with the other solutions provided by the other cloud service providers in the market."
"When scaling up, the pricing for Azure Stream Analytics can get relatively high. Considering its capabilities compared to other solutions, I would rate it a seven out of ten for cost. However, we've found ways to optimize costs using tools like Databricks for specific tasks."
"The cost of this solution is less than competitors such as Amazon or Google Cloud."
"The licensing for this product is payable on a 'pay as you go' basis. This means that the cost is only based on data volume, and the frequency that the solution is used."
"There are different tiers based on retention policies. There are four tiers. The pricing varies based on steaming units and tiers. The standard pricing is $10/hour."
"I rate the price of Azure Stream Analytics a four out of five."
"Azure Stream Analytics is a little bit expensive."
"The current price is substantial."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
15%
Manufacturing Company
7%
Healthcare Company
5%
Computer Software Company
15%
Financial Services Firm
14%
Manufacturing Company
10%
Retailer
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Flink?
The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. ...
What is your experience regarding pricing and costs for Apache Flink?
The solution is expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.
What needs improvement with Apache Flink?
There are more libraries that are missing and also maybe more capabilities for machine learning. It could have a friendly user interface for pipeline configuration, deployment, and monitoring.
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What is your experience regarding pricing and costs for Azure Stream Analytics?
I have no problem with pricing. We sell the data analytics value and operational value to customers, focusing on productivity and efficiency from the cloud, rather than just the infrastructure or p...
What needs improvement with Azure Stream Analytics?
There is a lack of technical support from Microsoft's local office, particularly in Taiwan. We often have to learn online, and language can be a communication barrier since not many IT staff can sp...
 

Also Known As

Flink
ASA
 

Overview

 

Sample Customers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
Find out what your peers are saying about Apache Flink vs. Azure Stream Analytics and other solutions. Updated: April 2025.
848,716 professionals have used our research since 2012.