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Azure Stream Analytics Reviews

Vendor: Microsoft
3.9 out of 5
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What is Azure Stream Analytics?

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.

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Azure Stream Analytics is the #4 ranked solution in Streaming Analytics tools. PeerSpot users give Azure Stream Analytics an average rating of 7.8 out of 10. Azure Stream Analytics is most commonly compared to Databricks: Azure Stream Analytics vs Databricks. Azure Stream Analytics is popular among the large enterprise segment, accounting for 68% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 14% of all views.
Buyer's Guide
Azure Stream Analytics
August 2025
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Azure Stream Analytics mindshare

As of August 2025, the mindshare of Azure Stream Analytics in the Streaming Analytics category stands at 8.8%, down from 12.5% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Azure Stream Analytics8.8%
Apache Flink14.5%
Databricks13.5%
Other63.2%
Streaming Analytics

PeerResearch reports based on Azure Stream Analytics reviews

TypeTitleDate
CategoryStreaming AnalyticsAug 29, 2025Download
ProductReviews, tips, and advice from real usersAug 29, 2025Download
ComparisonAzure Stream Analytics vs DatabricksAug 29, 2025Download
ComparisonAzure Stream Analytics vs Amazon KinesisAug 29, 2025Download
ComparisonAzure Stream Analytics vs ConfluentAug 29, 2025Download
Suggested products
TitleRatingMindshareRecommending
Databricks4.113.5%96%92 interviewsAdd to research
Confluent4.18.3%95%23 interviewsAdd to research
 
 
Key learnings from peers

Valuable Features

Azure Stream Analytics offers valuable features such as real-time analytics, SQL query capability, machine learning functionality, and seamless integration with Azure and Microsoft tools. Users appreciate its user-friendly interface, scalability, flexibility in data processing, and ease of configuration. It supports various technologies like IoT hub and Blob storage, providing efficient data management and visualization. The platform's cost-effectiveness and minimal learning curve enhance its appeal for enterprises seeking agile data solutions.
  • "The best features of Azure Stream Analytics are that it's easy to set up and configure."
  • "Cloud tools and cloud services enable flexibility and lower entry barriers for Taiwanese enterprises."
  • "Any time I needed assistance, they were helpful."

Room for Improvement

Azure Stream Analytics users face challenges with pricing transparency and detailed logging. Compatibility with Microsoft Power BI is sometimes unreliable and real-time data joining is limited. The interface may be complex for non-technical users, and scalability could improve. More flexible query capabilities and an extended free trial are desired. Users suggest enhancements in data validation, third-party tool support, and market presence. There is a need for more intuitive UI and better integration capabilities with other vendors.
  • "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."
  • "There is a lack of technical support from Microsoft's local office, particularly in Taiwan."
  • "There are too many products in the Azure landscape, which sometimes leads to overlap between them."

ROI

Azure Stream Analytics offers a quick setup for streaming pipelines with no upfront capital due to its cloud-based nature. Many users note a positive return on investment, estimating around 10%, largely because it enables swift delivery of solutions. Satisfaction among customers highlights its effectiveness, though some team members are not privy to specific financial arrangements, as these are managed by higher-level staff such as product or delivery managers.

Pricing

Azure Stream Analytics pricing is competitive compared to Amazon and Google Cloud but higher than open-source options. It is charged per hour or streaming unit, with potential confusion in billing. While more expensive for large-scale enterprise use, it remains efficient and cost-effective for small-scale needs. Prices may vary by region, with options like three-year upfront payment reducing costs. Users consider its price fair given its features, though some find it slightly higher than anticipated.
  • "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 product's price is at par with the other solutions provided by the other cloud service providers in the market."
  • "Azure Stream Analytics is a little bit expensive."

Popular Use Cases

Azure Stream Analytics is utilized to ingest real-time data streams into permanent storage. It processes and analyzes IoT data and sensor logs to enhance business operations. Organizations use it for tracking logistics, accident prevention, and predictive maintenance. It integrates with Power BI for data visualization and supports machine learning models. They employ it for telemetry data management and diagnostics, benefiting from its capability to handle vast datasets efficiently across multiple devices and locations.

Service and Support

Customers find Azure Stream Analytics' support helpful and very responsive. Technical support typically replies within 24 hours, and support engineers resolve challenges effectively. Many users rely on Azure's community forums, virtual documentation, and internal resources for assistance. Satisfaction levels vary, with some citing language or communication issues. The quality of help often depends on the subscription level. Users value Microsoft's knowledgeable service, but rising demand might impact support quality.

Deployment

Many describe Azure Stream Analytics's initial setup as straightforward and quick, aided by clear documentation and available templates. Some note its complexity increases with advanced configurations or hardware requirements. Familiarity with Azure simplifies the process, but inexperienced teams may struggle. Deployment is generally easy and fast, often completed in minutes, and benefits from automation tools. When IoT hardware is involved, additional maintenance may be necessary. Scalability and smooth connectivity are positively mentioned.

Scalability

Azure Stream Analytics is noted for its scalability, handling thousands of users across diverse organizations. It's cloud-based, enabling easy expansion by adding resources. Adaptability aligns with specific needs, influenced by cost and resource allocation. Some teams mention effective scalability, rating it highly, while acknowledging that costs vary with task complexity. Personnel are needed for maintenance, but solutions generally integrate well within existing IT environments, benefiting companies of different sizes and industries.

Stability

Azure Stream Analytics is regarded as stable, with users noting reliability and few bugs. Some reported occasional VM issues, job errors, or instability with older versions. Its performance is optimal within Azure, though manual resource tuning is needed for complex transformations. Users appreciate improvements over time and find Microsoft's support helpful. Stability ratings vary, with some giving high scores, while others seek improvements, especially after experiencing initial challenges or specific scenarios causing disruption.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Azure Stream Analytics Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
Company SizeCount
Small Business8
Midsize Enterprise3
Large Enterprise16
By reviewers
By visitors reading reviews
Company SizeCount
Small Business134
Midsize Enterprise66
Large Enterprise427
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
14%
Manufacturing Company
9%
Retailer
6%
Insurance Company
6%
Comms Service Provider
6%
University
5%
Educational Organization
4%
Healthcare Company
4%
Government
3%
Energy/Utilities Company
3%
Hospitality Company
3%
Media Company
3%
Performing Arts
2%
Non Profit
2%
Real Estate/Law Firm
2%
Construction Company
2%
Legal Firm
2%
Consumer Goods Company
2%
Transportation Company
1%
Wholesaler/Distributor
1%
Outsourcing Company
1%
Logistics Company
1%
Photography Company
1%
Mining And Metals Company
1%
Marketing Services Firm
1%

Compare Azure Stream Analytics with alternative products

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Learn more about Azure Stream Analytics

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

Azure Stream Analytics was previously known as ASA.

Azure Stream Analytics customers

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

Related questions

  • 63
Which would you choose - Databricks or Azure Stream Analytics?
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  • 22
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  • 44
What are the benefits of streaming analytics tools?
  • 56
What features do you look for in a streaming analytics tool?
  • 13
When evaluating Streaming Analytics, what aspect do you think is the most important to look for?
  • 15
Why is Streaming Analytics important for companies?

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Azure Stream Analytics Reviews Summary
Author infoRatingReview Summary
Director, Governance & Infrastructure & Director at VASS3.5I extensively work with Microsoft Azure and find it easy due to its native connectors and integration. However, the Azure landscape's complexity and licensing confusion are issues, prompting me to explore other options like Palantir for more efficient solutions.
Data Strategist, Cloud Solutions Architect at BiTQ4.0I use Azure Stream Analytics for processing telemetry data from mining sensors, aiding in predictive maintenance. Its easy setup and SQL-like query language are beneficial, though initial learning and integration with other services like Power BI were challenging.
DevSecOps Manager at APGecommerce2.5I used Azure Stream Analytics mainly for basic monitoring, but it lacked deep insights and automation. While it helped identify issues, it wasn't very comprehensive, and I rate it 5 out of 10 for monitoring capabilities.
PU Head of Manufacturing Industry at Wiadvance Technology Co3.5I use Azure Stream Analytics for data governance and ERP analytics, benefiting from its flexible service models like automation learning. However, there is a lack of local technical support in Taiwan, causing language barriers and limited useful case references.
Program Manager at a manufacturing company with 10,001+ employees2.5Azure Stream Analytics is valuable for managing telemetry data in real-time IoT scenarios, offering flexible SQL options. However, it lacks query flexibility and third-party support. Previously, I considered solutions like Databricks due to its superior structured streaming capabilities.
Co-Founder at Mandelbulb Technologies3.5I use Azure Stream Analytics for real-time IoT data analysis in my company. However, making changes to the job requires stopping the entire stream, which is inefficient. Although Microsoft Fabric resolves some issues, improvements are still needed in stream processing capabilities.
Sr Manager at a transportation company with 10,001+ employees3.5We utilize Azure Stream Analytics for processing data from IT devices, appreciating its data organization and visualization capabilities. However, we desire improved scalability, detailed job monitoring, and enhanced data ingestion. We also leverage other Azure services for comprehensive solutions.
Manager | Advisory PI | Data & Analytics at a consultancy with 10,001+ employees4.0No summary available