Azure Stream Analytics vs Confluent comparison

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Azure Stream Analytics

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Executive SummaryUpdated on Dec 17, 2024

Confluent and Azure Stream Analytics compete in the streaming analytics space. Azure Stream Analytics holds a technical advantage due to its in-depth features, despite Confluent's favorable pricing and support.

Features: Confluent offers robust integrations, high throughput, and flexibility to adapt to various data environments. Azure Stream Analytics provides complex event processing, native integration with Azure services, and seamless data flow and analysis.

Room for Improvement: Confluent's customer support could improve and its numerous configurations might overwhelm new users. Scalability for very large deployments can be complex, and documentation could be clearer. Azure Stream Analytics has high initial complexity, limited multi-cloud capabilities, and costs can escalate with feature expansions.

Ease of Deployment and Customer Service: Confluent is known for straightforward deployment and flexible configurations suitable for diverse IT ecosystems, but its customer support needs enhancement. Azure Stream Analytics offers simplified deployment within Azure, with strategic guidance for efficient implementation and reliable customer service for medium to large enterprises.

Pricing and ROI: Confluent presents a competitive pricing structure with good ROI, attracting businesses using open-source and streaming infrastructure. Azure Stream Analytics has higher initial setup costs with scalable pricing options, offering a balanced ROI through high-value data insights and efficiencies in Azure services.

To learn more, read our detailed Azure Stream Analytics vs. Confluent Report (Updated: December 2025).

Azure Stream Analytics vs. Confluent

December 2025

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Helped 881,707 peers since 2012

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

Azure Stream Analytics

Ranking in Streaming Analytics

4th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Confluent

Ranking in Streaming Analytics

5th

Average Rating

8.2

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Streaming Analytics category, the mindshare of Azure Stream Analytics is 5.8%, down from 11.4% compared to the previous year. The mindshare of Confluent is 6.8%, down from 8.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Azure Stream Analytics	5.8%
Confluent	6.8%
Other	87.4%

Streaming Analytics

Featured Reviews

Chandra Mani

Technical architect at Tech Mahindra

Has supported real-time data validation and processing across multiple use cases but can improve consumer-side integration and streamlined customization

I widely use AKS, Azure Kubernetes Service, Azure App Service, and there are APM Gateway kinds of things. I also utilize API Management and Front Door to expose any multi-region application I have, including Web Application Firewalls, and many more—around 20 to 60 services. I use Key Vault for managing secrets and monitoring Azure App Insights for tracing and monitoring. Additionally, I employ AI search for indexer purposes, processing chatbot data or any GenAI integration. I widely use OpenAI for GenAI, integrating various models with our platform. I extensively use hybrid cloud solutions to connect on-premise cloud or cloud to another network, employing public private endpoints or private link service endpoints. Azure DevOps is also on my list, and I leverage many security concepts for end-to-end design. I consider how end users access applications to data storage and secure the entire platform for authenticated users across various use cases, including B2C, B2B, or employee scenarios. I also widely design multi-tenant applications, utilizing Azure AD or Azure AD B2C for consumers. Azure Stream Analytics reads from any real-time stream; it's designed for processing millions of records every millisecond. They utilize Event Hubs for this purpose, as it allows for event processing. After receiving data from various sources, we validate and store it in a data store. Azure Stream Analytics can consume data from Event Hubs, applying basic validation rules to determine the validity of each record before processing.

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PavanManepalli

AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo

Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing

I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.

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Quotes from Members

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

Pros

"The most valuable aspect is the SQL option that Azure Stream Analytics provides."

"I extensively use hybrid cloud solutions to connect on-premise cloud or cloud to another network, employing public private endpoints or private link service endpoints."

"The support on critical issues depends on the level of subscription that you have with Microsoft itself; their support is very excellent, they understand the case immediately, they start to propose solutions and give you help, and if needed, they can work with you and you can connect with them just to explain more."

"It was easy for me to use from the beginning. I am accustomed to working with Microsoft."

"Technical support is pretty helpful."

"We find the query editor feature of this solution extremely valuable for our business."

"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."

"Azure Stream Analytics reads from any real-time stream; it's designed for processing millions of records every millisecond."

More Azure Stream Analytics pros

"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."

"We mostly use the solution's message queues and event-driven architecture."

"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."

"The monitoring module is impressive."

"The benefit is escaping email communication. Sometimes people ignore emails or put them into spam, but with Confluence, everyone sees the same text at the same time."

"Their tech support is amazing; they are very good, both on and off-site."

"The biggest benefit of Confluent as a tool is that it is a distributed platform that provides more durability and stability."

"Our main goal is to validate whether we can build a scalable and cost-efficient way to replicate data from these various sources."

More Confluent pros

Cons

"Azure Stream Analytics is challenging to customize because it's not very flexible."

"We would like to have centralized platform altogether since we have different kind of options for data ingestion. Sometimes it gets difficult to manage different platforms."

"The UI should be a little bit better from a usability perspective."

"The solution’s customer support could be improved."

"Easier scalability and more detailed job monitoring features would be helpful."

"More flexibility in terms of writing queries and accommodating additional facilities would be beneficial."

"Azure Stream Analytics could improve by having clearer metrics as to the scale, more metrics around the data set size that is flowing through it, and performance tuning recommendations."

"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."

More Azure Stream Analytics cons

"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."

"there is room for improvement in the visualization."

"Confluent has fallen behind in being the tool of the industry. It's taking second place to things such as Word and SharePoint and other office tools that are more dynamic and flexible than Confluent."

"The Schema Registry service could be improved. I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well."

"There is no local support team in Saudi Arabia."

"One area we've identified that could be improved is the governance and access control to the Kafka topics. We've found some limitations, like a threshold of 10,000 rules per cluster, that make it challenging to manage access at scale if we have many different data sources."

"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."

"Currently, in the early stages, I see a gap on the security side. If you are using the SaaS version, we would like to get a fuller, more secure solution that can be adopted right out of the box. Confluence could do a better job sharing best practices or a reusable pattern that others have used, especially for companies that can not afford to hire professional services from Confluent."

More Confluent cons

Pricing and Cost Advice

"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."

"The product's price is at par with the other solutions provided by the other cloud service providers in the market."

"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."

"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."

"Azure Stream Analytics is a little bit expensive."

More Azure Stream Analytics pricing and cost advice

"Confluent has a yearly license, which is a bit high because it's on a per-user basis."

"You have to pay additional for one or two features."

"Regarding pricing, I think Confluent is a premium product, but it's hard for me to say definitively if it's overly expensive. We're still trying to understand if the features and reduced maintenance complexity justify the cost, especially as we scale our platform use."

"On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs."

"It comes with a high cost."

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."

"Confluent is an expensive solution."

"Confluent is highly priced."

More Confluent pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

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881,707 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

11%

University

Manufacturing Company

Financial Services Firm

16%

Computer Software Company

11%

Retailer

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	3
Large Enterprise	18

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	4
Large Enterprise	16

Questions from the Community

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?

Azure charges in various ways based on incoming and outgoing data processing activities. Choosing between pay-as-you-go or enterprise models can affect pricing, and depending on data volume, charge...

What needs improvement with Azure Stream Analytics?

There is a need for improvement in reprocessing or validation without custom code. Azure Stream Analytics currently allows some degree of code writing, which could be simplified with low-code or no...

What do you like most about Confluent?

I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and to...

What is your experience regarding pricing and costs for Confluent?

They charge a lot for scaling, which makes it expensive.

What needs improvement with Confluent?

Amazon MSK vs Azure Stream Analytics

Comparisons

Compared 18% of the time

Apache Flink vs Azure Stream Analytics

Compared 14% of the time

Databricks vs Azure Stream Analytics

Compared 13% of the time

Amazon Kinesis vs Azure Stream Analytics

Compared 11% of the time

Apache Kafka vs Azure Stream Analytics

Compared 5% of the time

More Azure Stream Analytics Competitors

Palantir Foundry vs Confluent

Compared 14% of the time

Apache Flink vs Confluent

Compared 9% of the time

Amazon Kinesis vs Confluent

Compared 8% of the time

Databricks vs Confluent

Compared 6% of the time

Apache Kafka vs Confluent

Compared 2% of the time

More Confluent Competitors

Product Reports

Download Azure Stream Analytics product report

Azure Stream Analytics

February 2026

Download Confluent product report

February 2026

Also Known As

ASA

No data available

Overview

Azure Stream Analytics is a robust real-time analytics service that has been designed for critical business workloads. Users are able to build an end-to-end serverless streaming pipeline in minutes. Utilizing SQL, users are able to go from zero to production with a few clicks, all easily extensible with unique code and automatic machine learning abilities for the most advanced scenarios.

Azure Stream Analytics has the ability to analyze and accurately process exorbitant volumes of high-speed streaming data from numerous sources at the same time. Patterns and scenarios are quickly identified and information is gathered from various input sources, such as social media feeds, applications, clickstreams, sensors, and devices. These patterns can then be implemented to trigger actions and launch workflows, such as feeding data to a reporting tool, storing data for later use, or creating alerts. Azure Stream Analytics is also offered on Azure IoT Edge runtime, so the data can be processed on IoT devices.

Top Benefits

User friendly: Azure Stream Analytics is very straightforward and easy to use. Out of the box and with a few clicks, users are able to connect to numerous sources and sinks, and easily develop an end-to-end pipeline. Stream Analytics can easily connect to Azure IoT Hub and Azure Event Hub for streaming ingestion, in addition to connecting with Azure Blob storage for historical data ingestion.
Flexible deployment: For low-latency analytics, Azure Stream Analytics can run on Azure Stack or IoT edge. For large-scale analytics, the solution can run in the cloud. Azure Stream Analytics uses the same query language and tools for both the cloud and the edge, facilitating an easier process for developers to design exceptional hybrid architectures for streaming processes.
Cost-effective: With Azure Stream Analytics, users only pay for the streaming units they consume; there are no upfront costs. Users can easily scale up or down as needed; there is no commitment or cluster provisioning.
Trustworthy: Azure Stream Analytics guarantees event processing to be 99.99% available with a minute level of granularity. Azure Stream Analytics has embedded recovery capabilities and checkpoints to keep things running smoothly at all times. Events are never lost with Azure Stream Analytics at-least once delivery of events and exactly one event processing.

Reviews from Real Users

“Azure Stream Analytics is something that you can use to test out streaming scenarios very quickly in the general sense and it is useful for IoT scenarios. If I was to do a project with IoT and I needed a streaming solution, Azure Stream Analytics would be a top choice. The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex.” - Olubisi A., Team Lead at a tech services company.

“It's used primarily for data and mining - everything from the telemetry data side of things. It's great for streaming and makes everything easy to handle. The streaming from the IoT hub and the messaging are aspects I like a lot.” - Sudhendra U., Technical Architect at Infosys

Microsoft

Confluent is an enterprise-ready, full-scale streaming platform that enhances Apache Kafka.

Confluent has integrated cutting-edge features that are designed to enhance these tasks:

Speed up application development and connectivity
Enable transformations through stream processing
Streamline business operations at scale
Adhere to strict architectural standards

Confluent is a more complete distribution of Kafka in that it enhances the integration possibilities of Kafka by introducing tools for managing and optimizing Kafka clusters while providing methods for making sure the streams are secure. Confluent supports publish-and-subscribe as well as the storing and processing of data within the streams. Kafka is easier to operate and build thanks to Confluent.

Confluent's software is available in three different varieties:

A free, open-source streaming platform that makes it simple to start using real-time data streams
An enterprise-grade version of the product with more administrative, ops, and monitoring tools
A premium cloud-based version.

Confluent Advantage Features

Confluent has many valuable key features. Some of the most useful ones include:

Multi-language
- Clients: C++, Python, Go, and .NET
- REST proxy: Can connect to Kafka from any connected network device
- Admin REST APIs: RESTful interface for performing administrator operations

Pre-built ecosystem
- Connectors: More than 100 supported connectors, including S3, Elastic, HDFS, JDBC
- MQTT proxy: Gain access to Kafka from MQTT gateways and devices
- Schema registry: Centralized database to guarantee data compatibility

Streaming database
- ksqlDB: Materialized views and real-time stream processing

GUI management
- Control panel: GUI for scalable Kafka management and monitoring
- Health+: Smart alerts and cloud-based control centers

DevOps automation that is flexible
- Confluent for Kubernetes: Complete API to deploy on Kubernetes
- Automated Ansible deployment on non-containerized environments

Dynamic performance
- Self-balancing clusters: Automated partition re-balancing across brokers in the cluster
- Tiered storage: Older Kafka data offloading to object storage with transparent access

Security that is enterprise-grade
- Role-based access control: Granular user/group access authorization
- Audit logs that are structured: Logs of user actions kept in dedicated Kafka topics
- Secret protection: Sensitive information is encrypted

Global resilience
- Linking clusters: A real-time, highly reliable, and consistent bridge across on-premises and cloud environments
- Multiple-region clusters: Single Kafka cluster with automated client failover distributed across multiple data centers
- Replicator: Asynchronous replication that is based on the Kafka Connect framework

Support
- Round the clock enterprise support from Kafka experts

Reviews from Real Users

Confluent stands out among its competitors for a number of reasons. Two major ones are its robust enterprise support and its open source option. PeerSpot users take note of the advantages of these features in their reviews:

Ravi B., a solutions architect at a tech services company, writes of the solution, “KSQL is a valuable feature, as is the Kafka Connect framework for connecting to the various source systems where you need not write the code. We get great support from Confluent because we're using the enterprise version and whenever there's a problem, they support us with fine-tuning and finding the root cause.”

Amit S., an IT consultant, notes, “The biggest benefit is that it is open source. You have the flexibility of opting or not opting for enterprise support, even though the tool itself is open source.” He adds, “The second benefit is it's very modern and built on Java and Scala. You can extend the features very well, and it doesn't take a lot of effort to do so.”

Sample Customers

Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost