Azure Stream Analytics vs Starburst Galaxy comparison

Microsoft and Starburst are both solutions in the Streaming Analytics category. Microsoft is ranked #4 with an average rating of 7.1, while Starburst is ranked #12 with an average rating of 9.7. Microsoft holds a 7.6% mindshare in SA, compared to Starburst’s 1.3% 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

3,223 Views
2,933 Comparison Views

90% willing to recommend

Starburst Galaxy

Read 9 Starburst Galaxy reviews

616 Views
437 Comparison Views

100% willing to recommend

Azure Stream Analytics

Starburst Galaxy

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Stream Analytics and Starburst Galaxy based on real PeerSpot user reviews.

Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

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

Buyer's Guide

Azure Stream Analytics vs. Starburst Galaxy

September 2025

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Helped 869,202 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

Starburst Galaxy

Ranking in Streaming Analytics

12th

Average Rating

9.8

Reviews Sentiment

1.0

Number of Reviews

Ranking in other categories

Data Science Platforms (9th)

Mindshare comparison

As of October 2025, in the Streaming Analytics category, the mindshare of Azure Stream Analytics is 7.6%, down from 12.2% compared to the previous year. The mindshare of Starburst Galaxy is 1.3%, down from 1.3% 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	7.6%
Starburst Galaxy	1.3%
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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Stephen-Howard

Sr Director, Technology at Spreetail

Federated querying delivers integrated data at record speed and reduces processing time

The biggest win has been the ability to combine data from multiple sources and deliver it to the business at record speed. This capability has allowed us to query directly through Starburst Galaxy, enabling teams to access integrated data that would otherwise be hard to pull together. This has reduced both our ETL processing time and storage costs. We are answering questions that would have been hard, if not impossible, to answer previously because the data came from disparate, disconnected sources.

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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."

"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."

"It's easy to implement and maintain pipelines with minimal complexity."

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

"Cloud tools and cloud services enable flexibility and lower entry barriers for Taiwanese enterprises."

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

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

"It's scalable as a cloud product."

More Azure Stream Analytics pros

"Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."

"Starburst Galaxy serves as our primary SQL-based data processing engine, a strategic decision driven by its seamless integration with our AWS cloud infrastructure and its ability to deliver high performance with low-latency responses."

"Starburst Galaxy is becoming a cornerstone of our data platform, empowering us to make smarter and faster decisions across the organization."

"Starburst on Trino, combined with our SQL-native data transformation tool SQLMesh, has delivered anywhere from a two to five times improvement in compute performance across our transformation DAG."

"Starburst has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."

"The most fundamental feature is the query engine, which is much faster than any of the competitors; Starburst is able to finish most queries within 10 seconds, which is especially important for many non-technical employees."

Cons

"Regarding technical support for Azure Stream Analytics, it's not good."

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

"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."

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

"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."

"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-code platforms to enhance performance."

"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."

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

More Azure Stream Analytics cons

"Cluster startup time is another pain point, typically 3 to 5 minutes, which is not the worst with proper planning but can be annoying for ad-hoc work."

"The most persistent issue is the cluster spin-up time."

"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."

"Multi-tenancy could be improved. In order to have multiple environments for SSO, we maintain multiple tenants that are connected to different AWS accounts via the Marketplace."

"Cluster startup time can be slow, sometimes taking over a minute."

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."

"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."

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

"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."

"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 current price is substantial."

More Azure Stream Analytics pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

Insurance Company

Financial Services Firm

29%

Computer Software Company

14%

Government

Consumer Goods 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	4
Midsize Enterprise	2
Large Enterprise	1

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?

The solution does not need any license; it comes with your subscription.

See all answers

What needs improvement with Azure Stream Analytics?

With the deployment of Azure Stream Analytics, there are many challenges. I am working with a DevOps team that I'm part of as a counselor. I'm working with them because they are working in other pa...

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

You pay for cluster uptime. It is important to be aggressive about autoscaling, as a single worker will get you a long way. I recommend never connecting a BI tool to your Galaxy cluster. Instead, w...

See all answers

What needs improvement with Starburst Galaxy?

As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options. Trino is extremely flexible and powerful, but some of this fu...

See all answers

What is your primary use case for Starburst Galaxy?

I use Starburst as a cost-efficient hosted option for Trino for data integration and ad-hoc analysis across a broad range of data sources. It is surprisingly useful to query SQL Server, a Google Sh...

See all answers

Comparisons

Amazon MSK vs Azure Stream Analytics

Compared 23% of the time

Databricks vs Azure Stream Analytics

Compared 20% of the time

Apache Flink vs Azure Stream Analytics

Compared 18% of the time

Amazon Kinesis vs Azure Stream Analytics

Compared 16% of the time

Aiven Platform vs Azure Stream Analytics

Compared 5% of the time

More Azure Stream Analytics Competitors

Starburst Enterprise vs Starburst Galaxy

Compared 52% of the time

Databricks vs Starburst Galaxy

Compared 29% of the time

Dremio vs Starburst Galaxy

Compared 19% of the time

More Starburst Galaxy Competitors

Product Reports

Buyer's Guide

Azure Stream Analytics

October 2025

Download Azure Stream Analytics product report

Buyer's Guide

Starburst Galaxy

September 2025

Download Starburst Galaxy product report

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 Galaxy offers advanced analytics solutions tailored for big data environments. It is renowned for its scalability and flexibility, enabling data-driven decisions.

Starburst Galaxy provides an efficient platform for conducting complex data analysis across multiple datasets. Its architecture facilitates seamless integration with existing data infrastructure, allowing organizations to harness the value of their data efficiently. Users appreciate its ability to perform intricate queries without the need for extensive data movement, fostering a more agile approach to data management and analysis.

What features make Starburst Galaxy unique?

Advanced Query Engine: Optimizes data processing to handle complex analytics efficiently.
Scalability: Easily adapts to growing data needs without compromising performance.
Integration Capabilities: Seamlessly connects with existing data systems for streamlined operations.

What benefits and ROI should users look for?

Cost Efficiency: Reduces storage and compute costs by optimizing queries and minimizing data movement.
Improved Decision-Making: Empowers users with quick access to critical insights for strategic planning.
Enhanced Performance: Delivers faster query responses, boosting productivity and time-to-value.

Starburst Galaxy is instrumental in industries such as finance, healthcare, and e-commerce, where large-scale data analysis is crucial. Organizations in these fields implement its features to accelerate data processing and gain a competitive advantage, turning vast amounts of information into actionable insights that drive industry-specific innovations.

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 Galaxy

September 2025

Free Report: Azure Stream Analytics vs. Starburst Galaxy

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