Azure Stream Analytics vs Starburst Galaxy 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 #8 with an average rating of 9.5. Microsoft holds a 6.6% mindshare in SA, compared to Starburst’s 1.7% 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 Galaxy

Read 11 Starburst Galaxy reviews

1,953 Views
918 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: August 2026).

Buyer's Guide

Azure Stream Analytics vs. Starburst Galaxy

August 2026

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Helped 909,725 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

2nd

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

8th

Average Rating

9.4

Reviews Sentiment

2.5

Number of Reviews

Ranking in other categories

Data Science Platforms (7th)

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 Galaxy is 1.7%, up from 1.2% 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 Galaxy	1.7%
Other	91.7%

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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Niketan Kumar

Advisory Solutions Architect at Dell Technologies

Unified data querying has accelerated petabyte-scale analytics and simplified dashboard delivery

Starburst Galaxy offers me several best features, which include very fast querying results, automatic indexing of data for long tables, a cost-based optimizer which reduces the time to query large tables, and an agentic feature that lets me talk to my data.I find myself relying most on querying from different databases as well as automatic indexing in my day-to-day work, as I am a data science architect who needs to get the queries in a very short period of time. Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best. Starburst Galaxy has positively impacted my organization since we were struggling with Denodo and Dremio, which had their own features but were not helpful in querying large amounts of data, especially semi-structured or unstructured data. Starburst Galaxy addresses this with many YAML files and manifest files for automated maintenance, and it helps reduce the small file problem in different HDFS systems. Additionally, Starburst Galaxy has an MCP server that connects to various agentic pipelines, reducing the time to market for data consumption.

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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 features are the IoT hub and the Blob storage."

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

"The solution's technical support is good."

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

"The product is very user-friendly."

"It's scalable as a cloud product."

"From the end user's perspective, Stream Analytics forms the main backbone for the entire pipeline and all the technologies."

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

More Azure Stream Analytics pros

"Starburst Galaxy has significantly improved our data architecture flexibility and performance management by solving cross-database query challenges and enabling us to utilize iceberg tables externally across our entire data ecosystem."

"Starburst Galaxy has positively impacted my organization by allowing us to rethink the strategy for data and architect data differently; instead of having multiple data marts and siloed data marts, we have a unified vision, and that is how it is changing."

"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."

"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."

"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."

More Starburst Galaxy pros

Cons

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

"If something goes wrong, it's very hard to investigate what caused it and why."

"Having worked with some good monitoring tools, this is not that helpful as you cannot build analytics and predictions on these types of monitoring."

"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."

"The solution's interface could be simpler to understand for non-technical people."

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

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

"There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting."

More Azure Stream Analytics cons

"Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose."

"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."

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

"I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs."

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

"As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options."

"I think there are areas of improvement with respect to AI adaptability, and also in general, the amount of connectors working with other tools are areas where it can be expanded."

More Starburst Galaxy cons

Pricing and Cost Advice

"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 current price is substantial."

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

"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 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."

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

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

More Azure Stream Analytics pricing and cost advice

Information not available

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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

28%

Computer Software Company

11%

Construction Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	3

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...

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 is your experience regarding pricing and costs for Starburst Galaxy?

I recommend experimenting with different cluster sizes to determine what works best for your particular use case.

See all answers

What needs improvement with Starburst Galaxy?

Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose. We rely on third-party tools for ingesti...

See all answers

What is your primary use case for Starburst Galaxy?

My main use case for Starburst Galaxy is querying petabytes of data across vast data sources, and I use a federated query engine to join data sources from different databases and then join them usi...

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 Enterprise vs Starburst Galaxy

Compared 21% of the time

Databricks vs Starburst Galaxy

Compared 10% of the time

Dremio vs Starburst Galaxy

Compared 6% of the time

Qlik Talend Cloud vs Starburst Galaxy

Compared 6% of the time

Altair RapidMiner vs Starburst Galaxy

Compared 5% of the time

More Starburst Galaxy Competitors

Product Reports

Buyer's Guide

Azure Stream Analytics

August 2026

Download Azure Stream Analytics product report

Buyer's Guide

Starburst Galaxy

July 2026

Download Starburst Galaxy product report

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 Galaxy offers rapid query speeds and robust cluster management, enhancing data engineering efficiency while supporting AWS integrations and cross-database functionality. Users benefit from its advanced data integration and federated querying capabilities.

Starburst Galaxy stands out with a compute-focused architecture that excels in facilitating seamless data integration. Technological innovations like autoscaling clusters and automated metadata management optimize operations in multi-tenant environments. With a keen emphasis on compatibility, the platform provides support for AWS Glue and enables federated querying across S3, Snowflake, and Redshift. This adaptability ensures comprehensive ETL processes and enhances analytics through querying SQL Server, Google Sheets, and blob stores. While noted for its robust capabilities, users seek improvements in cluster startup times, Tableau and AI support, and desire infrastructure-as-code enhancements.

What are Starburst Galaxy's key features?

Rapid Query Speeds: Enhances data processing with quick responses.
Cluster Autoscaling: Optimizes resource allocation for varying workloads.
Federated Querying: Cross-database functionality for seamless integration.
Compute-Focused Architecture: Ensures efficiency and scalability.
Automated Metadata Management: Streamlines data handling processes.
AWS Integration: Broad compatibility with AWS services.

What benefits should users evaluate in reviews?

Data Engineering Efficiency: Reduces operating expenses and improves productivity.
Cost Reduction: Highlights lower storage costs with efficient data handling.
Seamless Integration: Enables robust data integration across various platforms.
Cluster Management: Supports diverse workloads with advanced management tools.

In industries focusing on large-scale data efforts, Starburst Galaxy plays an essential role in connecting data sources like Amazon S3 and RDS, streamlining tasks in data engineering and ad-hoc analysis across complex environments. Teams leverage its cross-database querying to boost AWS analytics, with features tailored for sectors needing agile data solutions, from ETL pipelines to secure data federation.

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

August 2026

Free Report: Azure Stream Analytics vs. Starburst Galaxy

Find out what your peers are saying about Azure Stream Analytics vs. Starburst Galaxy and other solutions. Updated: August 2026.

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