Starburst Galaxy vs Upsolver comparison

Starburst and Upsolver are both solutions in the Streaming Analytics category. Starburst is ranked #8 with an average rating of 9.5, while Upsolver is ranked #21 with an average rating of 8.5. Starburst holds a 1.7% mindshare in SA, compared to Upsolver’s 1.2% mindshare. Additionally, 100% of Starburst users are willing to recommend the solution, compared to 100% of Upsolver users who would recommend it.

Starburst Galaxy

Read 11 Starburst Galaxy reviews

1,809 Views
850 Comparison Views

100% willing to recommend

Upsolver

Read 4 Upsolver reviews

1,819 Views
455 Comparison Views

100% willing to recommend

Starburst Galaxy

Upsolver

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Starburst Galaxy and Upsolver 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 Starburst Galaxy vs. Upsolver Report (Updated: June 2026).

Buyer's Guide

Starburst Galaxy vs. Upsolver

June 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

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 (6th)

Upsolver

Ranking in Streaming Analytics

21st

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Integration (38th)

Mindshare comparison

As of July 2026, in the Streaming Analytics category, the mindshare of Starburst Galaxy is 1.7%, up from 1.3% compared to the previous year. The mindshare of Upsolver is 1.2%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Starburst Galaxy	1.7%
Upsolver	1.2%
Other	97.1%

Streaming Analytics

Featured Reviews

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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reviewer2784462

Software Engineer at a tech vendor with 10,001+ employees

Streaming pipelines have become simpler and onboarding new data sources is now much faster

One of the best features Upsolver offers is the automatic schema evolution. Another good feature is SQL-based streaming transformations. Complex streaming transformations such as cleansing, deduplication, and enrichment were implemented using SQL and drastically reduced the need for custom Spark code. My experience with the SQL-based streaming transformations in Upsolver is that it had a significant positive impact on the overall data engineering workflow. By replacing custom Spark streaming jobs with declarative SQL logic, I simplified development, review, and deployment processes. Data transformations such as parsing, filtering, enrichment, and deduplication could be implemented and modified quickly without rebuilding or redeploying complex code-based pipelines. Upsolver has impacted my organization positively because it brings many benefits. The first one is faster onboarding of new data sources. Another one is more reliable streaming pipelines. Another one is near-real-time data availability, which is very important for us. It also reduced operational effort for data engineering teams. A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days. Custom Spark code reduction reached 50 to 40 percent. Pipeline failures are reduced by 70 to 80 percent. Data latency is improved from hours to minutes.

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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

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

"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."

"I am now able to answer questions in a couple of minutes that would otherwise take hours or days of time for my data engineering teams."

"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."

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

More Starburst Galaxy pros

"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."

"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."

"Customer service is excellent, and I would rate it between eight point five to nine out of ten."

"A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days, custom Spark code reduction reached 50 to 40 percent, pipeline failures are reduced by 70 to 80 percent, and data latency is improved from hours to minutes."

"I have saved 50 to 60% on maintaining pipelines since using Upsolver."

Cons

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

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

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

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

"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."

"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."

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

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

More Starburst Galaxy cons

"I would say Upsolver's scalability is eight out of 10 because of pricing."

"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."

"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."

"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."

"There is room for improvement in query tuning."

Pricing and Cost Advice

Information not available

"Upsolver is affordable at approximately $225 per terabyte per year."

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Top Industries

By visitors reading reviews

Financial Services Firm

29%

Computer Software Company

12%

Construction Company

University

Real Estate/Law Firm

15%

Manufacturing Company

15%

Retailer

11%

Construction Company

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

No data available

Questions from the Community

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...

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What is your experience regarding pricing and costs for Upsolver?

My experience with pricing, setup cost, and licensing is that the pricing is nine out of 10.

See all answers

What needs improvement with Upsolver?

I think Upsolver can be improved with deeper integration with external orchestration out of the box. I would appreciate more clear dashboards with billing in real time as a needed improvement.

See all answers

What is your primary use case for Upsolver?

My main use case for Upsolver is to operate with changes in the structure of new data without a pipeline disrupting. I write SQL queries in Upsolver, and the platform takes care of the data itself,...

See all answers

Comparisons

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Altair RapidMiner vs Starburst Galaxy

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Compared 11% of the time

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Compared 10% of the time

SAS Access vs Upsolver

Compared 8% of the time

Alteryx Designer vs Upsolver

Compared 7% of the time

Rivery vs Upsolver

Compared 7% of the time

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Product Reports

Buyer's Guide

Starburst Galaxy

June 2026

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Buyer's Guide

Data Integration

June 2026

Download Upsolver product report

Overview

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

Upsolver offers a data lakehouse platform that simplifies big data processing and analytics, enabling data teams to efficiently handle large-scale datasets.

Upsolver's platform focuses on simplifying the complexities of data engineering by transforming raw data into queryable formats quickly. It allows seamless integration with cloud storage and various database systems, providing flexibility for data-driven businesses. The platform automates data preparation tasks, reducing manual coding and allowing teams to focus on extracting insights. Its scalable architecture supports real-time analytics and batch processing.

What are the key features of Upsolver?

Data Ingestion: Easily ingest data from multiple sources with minimal configuration.
Schema On-Read: Automatically interpret data schemas, simplifying data management.
Streaming SQL: Transform and analyze streaming data using a familiar SQL syntax.
Data Lake Integration: Seamlessly connect with data lakes for streamlined workflows.

What benefits and ROI should users consider?

Time Savings: Faster data processing reduces time to insights.
Cost Efficiency: Scalable architecture optimizes infrastructure costs.
Scalability: Handle growing data volumes effortlessly.
Flexibility: Supports wide data storage and processing strategies.

In the e-commerce industry, Upsolver helps businesses optimize their data pipelines for better customer segmentation and personalization, while in finance, it enhances fraud detection capabilities through real-time data analytics.

Upsolver

Buyer's Guide

Starburst Galaxy vs. Upsolver

June 2026

Free Report: Starburst Galaxy vs. Upsolver

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