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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
4th
Average Rating
7.8
Reviews Sentiment
6.9
Number of Reviews
18
Ranking in other categories
No ranking in other categories
Azure Stream Analytics
Ranking in Streaming Analytics
5th
Average Rating
7.8
Reviews Sentiment
6.5
Number of Reviews
29
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2025, in the Streaming Analytics category, the mindshare of Apache Flink is 14.6%, up from 10.1% compared to the previous year. The mindshare of Azure Stream Analytics is 8.1%, down from 12.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Flink14.6%
Azure Stream Analytics8.1%
Other77.3%
Streaming Analytics
 

Featured Reviews

Aswini Atibudhi - PeerSpot reviewer
Enables robust real-time data processing but documentation needs refinement
Apache Flink is very powerful, but it can be challenging for beginners because it requires prior experience with similar tools and technologies, such as Kafka and batch processing. It's essential to have a clear foundation; hence, it can be tough for beginners. However, once they grasp the concepts and have examples or references, it becomes easier. Intermediate users who are integrating with Kafka or other sources may find it smoother. After setting up and understanding the concepts, it becomes quite stable and scalable, allowing for customization of jobs. Every software, including Apache Flink, has room for improvement as it evolves. One key area for enhancement is user-friendliness and the developer experience; improving documentation and API specifications is essential, as they can currently be verbose and complex. Debugging and local testing pose challenges for newcomers, particularly when learning about concepts such as time semantics and state handling. Although the APIs exist, they aren't intuitive enough. We also need to simplify operational procedures, such as developing tools and tuning Flink clusters, as these processes can be quite complex. Additionally, implementing one-click rollback for failures and improving state management during dynamic scaling while retaining the last states is vital, as the current large states pose scaling challenges.
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

"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 is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."
"The setup was not too difficult."
"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"Apache Flink's best feature is its data streaming tool."
"The documentation is very good."
"The way it organizes data into tables and dashboards is very helpful."
"The solution's technical support is good."
"The most valuable features are the IoT hub and the Blob storage."
"The solution's most valuable feature is its ability to create a query using SQ."
"It was easy for me to use from the beginning. I am accustomed to working with Microsoft."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"The most valuable aspect is the SQL option that Azure Stream Analytics provides."
"It's scalable as a cloud product."
 

Cons

"There is a learning curve. It takes time to learn."
"There is room for improvement in the initial setup process."
"The state maintains checkpoints and they use RocksDB or S3. They are good but sometimes the performance is affected when you use RocksDB for checkpointing."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"In a future release, they could improve on making the error descriptions more clear."
"Apache Flink is very powerful, but it can be challenging for beginners because it requires prior experience with similar tools and technologies, such as Kafka and batch processing."
"Apache Flink's documentation should be available in more languages."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"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 doesn't handle large data packets very efficiently, which could be improved upon."
"One area that could use improvement is the handling of data validation. Currently, there is a review process, but sometimes the validation fails even before the job is executed. This results in wasted time as we have to rerun the job to identify the failure."
"There is a lack of technical support from Microsoft's local office, particularly in Taiwan."
"Easier scalability and more detailed job monitoring features would be helpful."
"If something goes wrong, it's very hard to investigate what caused it and why."
"There were challenges with Azure Stream Analytics. When I initially started, the learning curve was difficult because I didn't have knowledge of the service."
"Its features for event imports and architecture could be enhanced."
 

Pricing and Cost Advice

"This is an open-source platform that can be used free of charge."
"Apache Flink is open source so we pay no licensing for the use of the software."
"It's an open-source solution."
"The solution is open-source, which is free."
"It's an open source."
"The product's price is at par with the other solutions provided by the other cloud service providers in the market."
"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."
"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."
"Azure Stream Analytics is a little bit expensive."
"The current price is substantial."
"I rate the price of Azure Stream Analytics a four out of five."
"We pay approximately $500,000 a year. It's approximately $10,000 a year per license."
"The cost of this solution is less than competitors such as Amazon or Google Cloud."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Computer Software Company
11%
Retailer
11%
Manufacturing Company
7%
Financial Services Firm
14%
Computer Software Company
14%
Manufacturing Company
8%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise3
Large Enterprise11
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise3
Large Enterprise17
 

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?
Apache should provide more examples and sample code related to streaming to help me better adapt and utilize the tool. There is a need for increased awareness and education, especially around best ...
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?
The solution does not need any license; it comes with your subscription.
What needs improvement with Azure Stream Analytics?
It does not always give you the right reason or the correct reason. For example, if a service is stopped, it just tells you that it stopped and started. It does not give you any good insight as to ...
 

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: July 2025.
867,370 professionals have used our research since 2012.