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Rivery vs dbt comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

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)
Rivery
Ranking in Data Integration
25th
Average Rating
8.0
Reviews Sentiment
6.5
Number of Reviews
8
Ranking in other categories
Migration Tools (3rd), Cloud Migration (11th), Cloud Data Integration (15th)
 

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 Rivery is 0.6%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
dbt1.7%
Rivery0.6%
Other97.7%
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.
AD
CDL at Ycotek
Training has boosted custom ETL scripting and now debugging complex incremental loads needs work
The best feature Rivery offers is the ability to build custom or user-defined functions. You can even develop Python scripts to perform transformations on your data frames. This flexibility allows you to implement custom requirements, making Rivery more versatile than relying solely on in-built functions. Regarding features such as the interface, scheduling, or connectors, I found that as of 2022 when I last used it, the monitoring was good, although the debugging process for custom scripts was somewhat challenging. If we encountered issues with custom-built scripts, debugging was difficult since it used to send standard errors rather than specific ones. From what I recall, monitoring worked well, and we could connect to multiple relational and other sources, which was advantageous. A few of my colleagues and I were able to earn certifications on Rivery, which motivated us, even though we could not pursue or implement Rivery project for clients. The learning experience was very valuable as we had around seven or eight resources participating in those trainings, and they were all excited to learn about this new tool for us at the time.

Quotes from Members

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

Pros

"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."
"The product is developer-friendly."
"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."
"From a developer point of view, I find the ease of development and the code to be the most useful capabilities of dbt."
"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."
"The main benefit Rivery brought to my organization was the time we were able to save on development, and by using all these automation features provided by Rivery together with integration to Snowflake, we were able to solve problems."
"Connects to many APIs in the market and new ones are being added all the time."
"Rivery has positively impacted my organization by enabling us to create a stable pipeline, and we can expand the variety of the data sources as we go very easily, with no worries, and with a lot of confidence in the fact that it can be done."
"Rivery has positively impacted my organization by helping me streamline my data ingestion and transformation processes, especially in combination with Snowflake."
"Anyone looking into using Rivery should know it is a great product."
"The solution's most valuable features are that it is quick to connect and simple to use."
"Rivery has positively impacted my organization by reducing the need for a big team of data engineers and speeding up the work when we need to connect to a new data source; this can happen really fast."
"The process of using Rivery has worked very smoothly for me, and I found the tool very easy to use, allowing me to gain a lot of insights."
 

Cons

"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."
"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."
"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."
"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."
"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."
"The solution must add more Python-based implementations."
"The key challenges I recall were related to the incremental merging logic, which was not functioning properly."
"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."
"My experience with pricing, setup cost, and licensing was unfortunately not so good in my recent data project."
"As an end user of Rivery, I would like to see it be less commercial for users."
"Rivery can be improved by generally investing a bit more depth into the product, mainly in orchestration and specific features comparable to mature products."
"I think Rivery could be improved by having more analytical features inside."
"Lineage and an impact analysis or logic dependency are lacking."
 

Pricing and Cost Advice

"The solution’s pricing is affordable."
"I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Insurance Company
8%
Manufacturing Company
8%
Computer Software Company
7%
Manufacturing Company
12%
Comms Service Provider
11%
Real Estate/Law Firm
7%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise3
Large Enterprise3
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise3
 

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 Rivery?
I do not know about the experience with pricing, setup cost, and licensing as it was not part of my job.
What needs improvement with Rivery?
I think Rivery could be improved by having more analytical features inside. I do not know if in the latest updates there are some AI tools to use or something related to that. Sometimes I wish for ...
What is your primary use case for Rivery?
My main use case for Rivery involves collecting data from different sources, and with Rivery, I am able to put them together and load the data directly in Snowflake.
 

Comparisons

 

Overview

Find out what your peers are saying about Rivery vs. dbt and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.