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Upsolver vs dbt comparison

 

Comparison Buyer's Guide

Executive Summary

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

dbt
Ranking in Data Integration
17th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
7
Ranking in other categories
Data Quality (6th)
Upsolver
Ranking in Data Integration
37th
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
3
Ranking in other categories
Streaming Analytics (21st)
 

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of dbt is 1.7%, up from 1.0% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
dbt1.7%
Upsolver0.7%
Other97.6%
Data Integration
 

Featured Reviews

AS
Principal Data Engineer at Integrant, Inc.
Data teams have streamlined code-driven pipelines and now collaborate faster on shared models
We are still experimenting with testing, but not that much. We are not using some features yet. We are trying to introduce them because we are coming from a background of SSIS. The team used to work with SSIS, Microsoft SQL Server Integration Services. We are still adapting one feature at a time. Currently, we are working with the SQL modules and with the Jinja templating. We are experimenting with testing, but I would say towards the end of this year, we are planning to explore more of the documentation and the data lineage options as well. I would say the benefits are coming from GUI-based tools like SSIS. We have more control on the codebase. We can create something of a system where we can use macros and templating, speeding up the development cycle. We are now trying to introduce a little testing, and also we are using some sort of a CI/CD cycle, so continuous integration and continuous deployment. I do not believe that these kinds of features are that common as a package as a whole package. dbt excels in that area. I used to have a couple of notes about the performance, but lately I have discovered something called dbt Fusion, which, according to dbt Labs, they proclaim is much faster during the parsing of dbt models. However, I would love to see even more of an out-of-the-box solution regarding the testing. They are treating the testing in a good way so far, but I would love to see even more improvement because the whole data testing field is not very mature. It is not the same as software testing; for example, you have test suites, test tools, and profilers, but for data testing, it is not yet that advanced. I would love for dbt to take the lead on that.
reviewer2784462 - PeerSpot reviewer
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Since we migrated from SSIS to dbt model architecture, it takes around four hours only to complete a full refresh, and the client is now happy because our downtime was drastically reduced when we perform a complete refresh of the data."
"I would say the best feature or the most desirable feature for dbt is the ability to write everything in code."
"There is operational efficiency achieved, and data quality and governance have also been achieved with modular SQL and version controlling, which reduced duplication of data and data errors."
"dbt has positively impacted my organization by allowing us to create our data pipelines much faster, going from ingestion of data to creating a data product in weeks instead of months, and we can do it in-house with the skillset we already have."
"From a developer point of view, I find the ease of development and the code to be the most useful capabilities of dbt."
"The product is developer-friendly."
"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."
"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."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
 

Cons

"The solution must add more Python-based implementations."
"Dbt is not as stable as preferred, as it has had a few outages in the current year itself, so improvement should be made in the outages section as it is not stable."
"If I needed to name a few areas for improvement, I would mention the migration of code to Git and GitHub, which sometimes fails and can be confusing for developers during handover."
"Every upgrade is a little bit of a risk for us because we do not know if the workarounds that we developed will be available for the next version."
"dbt can be improved as I find the co-pilot in dbt is not very good, and my team has tried using it but opted to move off it and use other co-pilots such as GitHub."
"Since dbt has a license cost, if a company is small and does not have much budget, they can explore other tools because there are other tools that provide the same functionality at a lower cost."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
"There is room for improvement in query tuning."
"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."
"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."
 

Pricing and Cost Advice

"The solution’s pricing is affordable."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Insurance Company
8%
Manufacturing Company
8%
Computer Software Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise3
Large Enterprise3
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for dbt?
The course content that dbt provides is free and excellent for anyone starting out.
What needs improvement with dbt?
We are still experimenting with testing, but not that much. We are not using some features yet. We are trying to introduce them because we are coming from a background of SSIS. The team used to wor...
What is your primary use case for dbt?
I am working with one of our enterprise customers, managing their newly established cloud warehouse. They are using Snowflake and we are using dbt to manage all the transformation and views and tab...
What is your experience regarding pricing and costs for Upsolver?
My experience with pricing, setup cost, and licensing was a very good experience, but it is not a direct experience because it was not my responsibility. It was in charge of the customer. However, ...
What needs improvement with Upsolver?
I think that Upsolver can be improved in orchestration because it is not a full orchestration tool. I believe it could be better in this regard. The cost needs attention at a very large scale. I th...
What is your primary use case for Upsolver?
My main use case for Upsolver is during an IT consulting project for a large enterprise running a cloud-native data platform on AWS. I used Upsolver to ingest and process high-volume stream data fr...
 

Comparisons

 

Overview

Find out what your peers are saying about Upsolver vs. dbt and other solutions. Updated: March 2026.
884,797 professionals have used our research since 2012.