StreamSets vs dbt comparison

dbt Labs and IBM are both solutions in the Data Integration category. dbt Labs is ranked #31 with an average rating of 7.5, while IBM is ranked #22 with an average rating of 9.0. dbt Labs holds a 2.1% mindshare in DI, compared to IBM’s 1.5% mindshare. Additionally, 100% of dbt Labs users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

dbt

Read 2 dbt reviews

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1,194 Comparison Views

100% willing to recommend

StreamSets

Read 21 StreamSets reviews

2,599 Views
1,871 Comparison Views

100% willing to recommend

dbt

StreamSets

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Executive SummaryUpdated on Dec 19, 2024

StreamSets and dbt are competing products in the data integration and transformation space. StreamSets has an advantage in customer service and pricing, while dbt holds the upper hand in its feature set, promising better long-term value.

Features: StreamSets offers robust data integration with real-time data processing, supports on-premise and cloud environments, and facilitates broad data handling. Dbt focuses on transformation within the warehouse, provides modular SQL development, version control, and specializes in SQL-based transformations.

Ease of Deployment and Customer Service: StreamSets allows for seamless integration with existing systems, with flexible deployment options across on-premise, cloud, and hybrid models. Their customer service is responsive and helpful. Dbt primarily focuses on cloud-based deployment, boasts strong documentation for ease of use, but may require more initial setup. Their SQL-only operations simplify deployment for some, though StreamSets offers greater deployment flexibility and support.

Pricing and ROI: StreamSets provides competitive pricing with various subscription models, offering lower initial costs and quicker ROI. Dbt may be more expensive at the outset; however, its advanced transformation capabilities are seen as a worthwhile investment for optimizing warehouse data, with a promise of long-term value. StreamSets has an advantage in initial cost-effectiveness, while dbt justifies higher costs with its comprehensive features.

To learn more, read our detailed StreamSets vs. dbt Report (Updated: September 2025).

Buyer's Guide

StreamSets vs. dbt

September 2025

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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

dbt

Ranking in Data Integration

31st

Average Rating

7.6

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

StreamSets

Ranking in Data Integration

22nd

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Data Integration category, the mindshare of dbt is 2.1%, up from 0.3% compared to the previous year. The mindshare of StreamSets is 1.5%, down from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
StreamSets	1.5%
dbt	2.1%
Other	96.4%

Data Integration

Featured Reviews

Ninad Magdum

Senior Machine Learning Engineer at Happiest Minds Technologies

Developer-friendly and easy to use, but doesn't have many optimization options

We also use stored procedures and Talend. They are not replaced by dbt completely. We use dbt only for the transformation process. My recommendations would depend on an organization’s requirements and problems. I will recommend the tool to others. The product is developer-friendly. However, it is still dependent on the data warehouse for big data and optimization. It's just a SQL transformation tool. It doesn't have a lot of optimization options like Spark. It's a good tool for Snowflake. If it were only for Snowflake, I would have rated it an eight out of ten. However, there are other data platforms. Overall, I rate the tool a six and a half out of ten.

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Ved Prakash Yadav

Senior Data Platform Manager at a manufacturing company with 10,001+ employees

Useful for data transformation and helps with column encryption

We use various tools and alerting systems to notify us of pipeline errors or failures. StreamSets supports data governance and compliance by allowing us to encrypt incoming data based on specified rules. We can easily encrypt columns by providing the column name and hash key. If you're considering using StreamSets for the first time, I would advise first understanding why you want to use it and how it will benefit you. If you're dealing with change tracking or handling large amounts of data, it could be cost-effective compared to services like Amazon. It's easy to schedule and manage tasks with the tool, and you can enhance your skills as an ETL developer. You can easily migrate traditional pipelines built on platforms like Informatica or Talend to StreamSets. I rate the overall solution an eight out of ten.

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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 product is developer-friendly."

"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."

"StreamSets is the leader in the market."

"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."

"I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."

"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"

"The best feature that I really like is the integration."

"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."

"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."

More StreamSets pros

Cons

"The solution must add more Python-based implementations."

"Visualization and monitoring need to be improved and refined."

"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."

"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."

"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."

"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."

"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."

"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."

"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."

More StreamSets cons

Pricing and Cost Advice

"The solution’s pricing is affordable."

"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

"StreamSets is an expensive solution."

"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."

"Its pricing is pretty much up to the mark. For smaller enterprises, it could be a big price to pay at the initial stage of operations, but the moment you have the Seed B or Seed C funding and you want to scale up your operations and aren't much worried about the funds, at that point in time, you would need a solution that could be scaled."

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."

"The pricing is affordable for any business."

"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Insurance Company

11%

Manufacturing Company

Outsourcing Company

Computer Software Company

10%

Financial Services Firm

Insurance Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	2
Large Enterprise	11

Questions from the Community

What is your experience regarding pricing and costs for dbt?

It is cheap because dbt is open source. If you compare the pay-per-service of Dbt with the open source option you can manage. We are managing the solution, when we were acquiring service from them....

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What needs improvement with dbt?

SQL statements that beyond DML, are not possible. Currently, they are not possible in Dbt. Having more features in SQL statements will support us. Another issue is the terms of data ingestion becau...

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What is your primary use case for dbt?

We use the solution to deal with data transformations inside different organizations.

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What do you like most about StreamSets?

The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...

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What needs improvement with StreamSets?

One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infr...

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What is your primary use case for StreamSets?

We are using StreamSets for batch loading.

See all answers

Comparisons

SSIS vs dbt

Compared 25% of the time

Informatica PowerCenter vs dbt

Compared 11% of the time

Oracle Data Integrator (ODI) vs dbt

Compared 9% of the time

Tobiko vs dbt

Compared 8% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs dbt

Compared 7% of the time

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Informatica PowerCenter vs StreamSets

Compared 11% of the time

webMethods.io vs StreamSets

Compared 8% of the time

IBM InfoSphere DataStage vs StreamSets

Compared 8% of the time

Qlik Replicate vs StreamSets

Compared 7% of the time

Oracle GoldenGate vs StreamSets

Compared 7% of the time

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Product Reports

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Data Integration

September 2025

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Buyer's Guide

StreamSets

September 2025

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Overview

dbt is a transformational tool that empowers data teams to quickly build trusted data models, providing a shared language for analysts and engineering teams. Its flexibility and robust feature set make it a popular choice for modern data teams seeking efficiency.

Designed to integrate seamlessly with the data warehouse, dbt enables analytics engineers to transform raw data into reliable datasets for analysis. Its SQL-centric approach reduces the learning curve for users familiar with it, allowing powerful transformations and data modeling without needing a custom backend. While widely beneficial, dbt could improve in areas like version management and support for complex transformations out of the box.

What are the most valuable features of dbt?

SQL-Based Development: Facilitates transformations using SQL, streamlining the data modeling process.
Modularity: Encourages reusable components, making projects easier to manage and scale.
Version Control: Integrates with version control systems to track changes and collaborate effectively.
Testing Framework: Ensures data quality through automated tests, increasing trust in data outputs.

What benefits should you expect from using dbt?

Efficiency: Cuts down data processing times, allowing faster access to insights.
Collaboration: Promotes teamwork through shared data models and a common working language.
Scalability: Supports growing data demands by transforming complex data more flexibly and modularly.
Transparency: Provides clear documentation and lineage tracking, aiding in troubleshooting and understanding.

In the finance industry, dbt helps in cleansing and preparing transactional data for analysis, leading to more accurate financial reporting. In e-commerce, it empowers teams to rapidly integrate and analyze customer behavior data, optimizing marketing strategies and improving user experience.

dbt Labs

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

IBM

Sample Customers

Information Not Available

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

StreamSets vs. dbt

September 2025

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