Azure Stream Analytics vs Starburst Enterprise comparison

Microsoft and Starburst are both solutions in the Streaming Analytics category. Microsoft is ranked #3 with an average rating of 7.1, while Starburst is ranked #16 with an average rating of 8.5. Microsoft holds a 6.2% mindshare in SA, compared to Starburst’s 3.2% mindshare. Additionally, 90% of Microsoft users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Azure Stream Analytics

Read 30 Azure Stream Analytics reviews

2,877 Views
2,618 Comparison Views

90% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,426 Views
856 Comparison Views

100% willing to recommend

Azure Stream Analytics

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Azure Stream Analytics and Starburst Enterprise are analytics products with various features catering to different user needs. While Azure Stream Analytics stands out for its pricing and support, Starburst Enterprise's advanced features justify its higher cost.

Features: Azure Stream Analytics specializes in real-time data processing with seamless integration into Microsoft's ecosystem. It supports complex queries and offers a scalable architecture. Starburst Enterprise provides high-performance SQL compatibility, querying across diverse data sources, and excels in both cloud and on-premise environments. The key difference is Azure's ecosystem integration versus Starburst's data source flexibility.

Ease of Deployment and Customer Service: Azure Stream Analytics offers a simple deployment through the Azure portal and benefits from Microsoft's robust service support. Starburst Enterprise, however, requires more expertise for setup due to its compatibility with various environments but offers excellent documentation and community support. Azure’s user-friendly deployment and integration surpass expectations for ease of use, while Starburst’s flexibility is favorable for multi-environment capabilities.

Pricing and ROI: Azure Stream Analytics presents competitive pricing models that are cost-effective, particularly for businesses within the Microsoft ecosystem. Starburst Enterprise, on the other hand, has a higher setup cost, commanding a premium for its extensive querying features and performance improvements. The investment in Starburst Enterprise offers significant ROI for organizations with complex data needs, while Azure is preferable for those seeking cost-effective Microsoft integrations.

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

Buyer's Guide

Azure Stream Analytics vs. Starburst Enterprise

December 2025

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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

3rd

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Starburst Enterprise

Ranking in Streaming Analytics

16th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Science Platforms (12th)

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Azure Stream Analytics is 6.2%, down from 11.6% compared to the previous year. The mindshare of Starburst Enterprise is 3.2%, up from 2.6% 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	6.2%
Starburst Enterprise	3.2%
Other	90.6%

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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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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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

"It's a product that can scale."

"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."

"Any time I needed assistance, they were helpful."

"The most valuable features are the IoT hub and the Blob storage."

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

"It's scalable as a cloud product."

"It provides the capability to streamline multiple output components."

"Azure Stream Analytics helps with processing fast-moving data in my IoT applications because it's quicker to escalate."

More Azure Stream Analytics pros

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

"It's very scalable, fast performing, and supports many catalogs."

Cons

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

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

"The collection and analysis of historical data could be better."

"The only challenge was that the streaming analytics area in Azure Stream Analytics could not meet our company's expectations, making it a component where improvements are required."

"The initial setup is complex."

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

"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."

"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

"There should be support for REST API data sources to access data from the web."

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

Pricing and Cost Advice

"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 current price is substantial."

"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."

"I rate the price of Azure Stream Analytics a four out of five."

"The cost of this solution is less than competitors such as Amazon or Google Cloud."

"We pay approximately $500,000 a year. It's approximately $10,000 a year per license."

"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."

More Azure Stream Analytics pricing and cost advice

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

11%

Manufacturing Company

University

Financial Services Firm

39%

Computer Software Company

Government

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

No data available

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...

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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...

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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...

See all answers

What is your experience regarding pricing and costs for Starburst Enterprise?

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

See all answers

What needs improvement with Starburst Enterprise?

See all answers

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

See all answers

Comparisons

Amazon MSK vs Azure Stream Analytics

Compared 19% of the time

Apache Flink vs Azure Stream Analytics

Compared 15% of the time

Databricks vs Azure Stream Analytics

Compared 15% of the time

Amazon Kinesis vs Azure Stream Analytics

Compared 12% of the time

Apache Spark Streaming vs Azure Stream Analytics

Compared 7% of the time

More Azure Stream Analytics Competitors

Databricks vs Starburst Enterprise

Compared 36% of the time

Starburst Galaxy vs Starburst Enterprise

Compared 17% of the time

Dremio vs Starburst Enterprise

Compared 14% of the time

Apache Flink vs Starburst Enterprise

Compared 7% of the time

Apache Spark Streaming vs Starburst Enterprise

Compared 6% of the time

More Starburst Enterprise Competitors

Product Reports

Buyer's Guide

Azure Stream Analytics

January 2026

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Buyer's Guide

Data Science Platforms

January 2026

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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

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

Starburst

Sample Customers

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

Information Not Available

Buyer's Guide

Azure Stream Analytics vs. Starburst Enterprise

December 2025

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