Azure Stream Analytics vs Starburst Enterprise comparison

Microsoft and Starburst are both solutions in the Streaming Analytics category. Microsoft is ranked #2 with an average rating of 6.7, while Starburst is ranked #19 with an average rating of 9.0. Microsoft holds a 6.6% mindshare in SA, compared to Starburst’s 2.3% 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

6,312 Views
5,870 Comparison Views

90% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

2,389 Views
1,314 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: August 2026).

Buyer's Guide

Azure Stream Analytics vs. Starburst Enterprise

August 2026

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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

2nd

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

19th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Science Platforms (16th)

Mindshare comparison

As of August 2026, in the Streaming Analytics category, the mindshare of Azure Stream Analytics is 6.6%, down from 8.7% compared to the previous year. The mindshare of Starburst Enterprise is 2.3%, down from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Azure Stream Analytics	6.6%
Starburst Enterprise	2.3%
Other	91.1%

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

"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."

"The biggest improvement for us has been that it now takes much less time for us to receive valuable information."

"It's scalable as a cloud product."

"This is a great product that works better than most of its competitors."

"It's great for streaming and makes everything easy to handle."

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

"The way it organizes data into tables and dashboards is very helpful."

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

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

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

"There is a lack of technical support from Microsoft's local office, particularly in Taiwan."

"There are some improvements that could be made, first of all in pricing, because right now the pricing is a bit unclear."

"We had some issues with the jobs not behaving properly. They promise a lot, however, sometimes that doesn't happen and we realized that later."

"There are too many products in the Azure landscape, which sometimes leads to overlap between them."

"Its features for event imports and architecture could be enhanced."

"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 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

"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."

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

Pricing and Cost Advice

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

"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."

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

"Azure Stream Analytics is a little bit expensive."

"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 current price is substantial."

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

12%

Manufacturing Company

Computer Software Company

Comms Service Provider

Financial Services Firm

34%

Computer Software Company

Manufacturing Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	3
Large Enterprise	17

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...

See all answers

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...

See all answers

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 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

What advice do you have for others considering Starburst Enterprise?

Starburst requires a heavy investment in infrastructure; it needs heavy computing and storage. If your use case doesn't involve heavy processing or storage, then Starburst might not be the solution...

See all answers

Comparisons

Databricks vs Azure Stream Analytics

Compared 12% of the time

Confluent vs Azure Stream Analytics

Compared 9% of the time

Apache Spark Streaming vs Azure Stream Analytics

Compared 9% of the time

Amazon Kinesis vs Azure Stream Analytics

Compared 8% of the time

Apache Flink vs Azure Stream Analytics

Compared 8% of the time

More Azure Stream Analytics Competitors

Starburst Galaxy vs Starburst Enterprise

Compared 17% of the time

Databricks vs Starburst Enterprise

Compared 11% of the time

Dremio vs Starburst Enterprise

Compared 7% of the time

Cloudera DataFlow vs Starburst Enterprise

Compared 6% of the time

Dataiku vs Starburst Enterprise

Compared 6% of the time

More Starburst Enterprise Competitors

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Azure Stream Analytics

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Data Science Platforms

August 2026

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Also Known As

ASA

No data available

Overview

Azure Stream Analytics offers real-time data processing with seamless IoT hub integration and user-friendly setup. It efficiently manages data streams and supports Azure services, SQL Server, and Cosmos DB.

Azure Stream Analytics specializes in real-time data analytics, easily integrating with Microsoft technologies. It enables swift deployment, monitoring, and high-performance data streaming. Though praised for its powerful SQL language and machine learning capabilities, users face challenges with historical analysis, pricing clarity, debugging, and data connection outside Azure. Limited real-time data joining, query customization, and complex data handling are noted alongside needs for improved technical support, job monitoring, and trial periods.

What are the key features of Azure Stream Analytics?

IoT Hub Integration: Seamless connection with IoT devices for efficient data stream management.
Real-Time Analytics: Capable of processing and analyzing vast data volumes instantly.
SQL-Based Language: Powerful language for simple and flexible query creation.
Azure Service Integration: Compatible with Azure Storage, SQL Server, Cosmos DB.
Interface: User-friendly setup and swift deployment for efficient monitoring.
Machine Learning: Enhanced capabilities support predictive and preventive data analysis.

What benefits or ROI should users consider?

High-Performance Streaming: Efficient throughput for real-time data applications.
Data Partitioning: Supports scalability and flexibility in processing large data sets.
Minimal Setup Requirements: Quick and easy deployment, reducing initial setup time.
Integration Ease: Compatibility with Microsoft technologies simplifies implementation.

Azure Stream Analytics is leveraged in industries for real-time IoT data processing, predictive analytics, and accident prevention in logistics. It supports telemetry data processing for applications like predictive maintenance and integrates with Power BI for enhanced data visualization, aligning with Azure's IoT infrastructure.

Microsoft

Starburst Enterprise optimizes data processing for businesses, offering a robust platform tailored for efficient data handling. Ideal for tech-savvy audiences, it powers seamless data analysis and management.

Starburst Enterprise provides an advanced infrastructure that simplifies querying massive data sets from a variety of sources. Its integration capabilities allow users to access and analyze data without extensive data movement, ensuring cost-effective operations and speedy insights. Businesses can leverage comprehensive data analytics strategies, significantly enhancing their decision-making processes while minimizing latency.

What are the key features of Starburst Enterprise?

Data Federation: Connects disparate data sources without consolidation.
High-Performance Query: Delivers fast, interactive SQL analytics even on diverse data sets.
Security and Access Control: Ensures data is protected with robust security protocols and user management systems.
Scalability: Capable of handling increasing workloads efficiently.

What benefits and ROI should users look for?

Cost Efficiency: Reduces data warehousing costs by querying data at its source.
Time Savings: Accelerates data access and query responses, improving productivity.
Scalability: Supports growing data needs effortlessly, reducing infrastructure investments.

In industries like finance and retail, Starburst Enterprise is implemented to streamline big data operations, enhance customer experiences, and facilitate better risk management. Its ability to integrate with existing infrastructures allows for seamless adoption into company operations, delivering substantial analytical advantages.

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

August 2026

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