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Teradata vs dbt comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 4, 2026

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)
Teradata
Ranking in Data Integration
13th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
83
Ranking in other categories
Customer Experience Management (6th), Backup and Recovery (16th), Relational Databases Tools (5th), Data Warehouse (3rd), BI (Business Intelligence) Tools (9th), Marketing Management (6th), Cloud Data Warehouse (3rd), Database Management Systems (DBMS) (5th)
 

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 Teradata is 0.9%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Teradata0.9%
dbt1.7%
Other97.4%
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.
David Durand Velásquez - PeerSpot reviewer
Engineers at a consultancy with 11-50 employees
Delivers consistent performance and enables advanced analytics across complex data environments
Teradata stands out as a solid platform for managing and analyzing large volumes of data. Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments. One of its most notable strengths is the ability to run complex queries at high speed, which is essential for organizations that require timely and reliable analytics. Teradata offers a well-integrated ecosystem that supports working with different types of data and enables scalability as organizational needs grow. Its focus on advanced analytics, integration with modern business intelligence tools, and the ability to operate both on-premise and in the cloud make it a versatile solution for data warehousing and large-scale processing. Teradata's stability, technological maturity, and the availability of strong documentation and best practices are noteworthy. I consider Teradata to be a tool with great potential for any organization looking to enhance its analytical capabilities, optimize data processing, and move toward more data-driven decision-making. Teradata stands out as a solid platform for managing a large volume of data in different projects. Its architecture allows information to be processed efficiently while maintaining stable performance, even in high-demanding environments. A well-integrated AI ecosystem that supports working with different types of data and enables scalability as organizational needs grow across different kinds of enterprises or organizations. The focus on advanced analytics integration with modern business intelligence tools is particularly valuable. Teradata combines a powerful parallel process and optimizing SQL engine with a highly scalable architecture allowing businesses to execute complex queries and analytics in real-time. It supports multi-cloud, hybrid, and on-premise environments, giving organizations flexibility to choose the setup that best aligns with their strategy. One of the biggest strengths is the ability to unify disparate data sources and support high concurrency, enabling different teams, such as analytics, operations, BI, and data science, to access consistent, trusted data across the enterprise.

Quotes from Members

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

Pros

"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."
"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."
"The product is developer-friendly."
"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."
"It is quick, secure, and has less hassles because we don't have to involve our networking team, infrastructure, etc. It is very easy to deploy and make market ready."
"Teradata's pretty fast."
"The most valuable feature of Teradata is security. It runs on Unix and Linux platforms which provide better security."
"The product's scalability is great. Scalability-wise, I rate the solution a ten out of ten."
"Designing the database is easy."
"Cuts time to process huge amounts of data with efficient analytical queries."
"It is a stable program."
"Teradata's best feature is its speed with historical data."
 

Cons

"The solution must add more Python-based implementations."
"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."
"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."
"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 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."
"The user interface needs to be improved."
"Sometimes the large injestion takes days to load data, and some of our stored procedures take two to three days."
"I choose 8 out of 10 for Teradata because there is always the scope for improvement."
"From my perspective, it would be good if they gave better ITIN/R plugins to use the data for AI modeling, or data science modeling. We can do it now; however, it could be more elegant in terms of interfacing."
"The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues."
"An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly."
"​Their level of technical support is adequate. It could be better.​"
"Azure Synapse SQL has evolved from a solely dedicated support tool to a data lake. It can store data from multiple systems, not just traditional database management systems. On the other hand, Teradata has limitations in loading flat files or unstructured data directly into its warehouse. In Azure Synapse SQL, we can implement machine learning using Python scripts. Additionally, Azure Synapse SQL offers advanced analytical capabilities compared to Teradata. Teradata is also expensive."
 

Pricing and Cost Advice

"The solution’s pricing is affordable."
"It is still a very expensive solution. While I very much like the pure technological supremacy of the software itself, I believe Teradata as a company needs to become more affordable. They are already losing the market to more flexible or cheaper competitors."
"The price of Teradata is on the higher side, and I think that it where they lose out on some of their business."
"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."
"Teradata is a very expensive solution."
"It's a very expensive product."
"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."
"It comes at a notably high cost for what it offers."
"The cost is significantly high."
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Comparison Review

it_user232068 - PeerSpot reviewer
Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Insurance Company
8%
Manufacturing Company
8%
Computer Software Company
7%
Financial Services Firm
20%
Manufacturing Company
8%
Computer Software Company
6%
Government
6%
 

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 Business28
Midsize Enterprise13
Large Enterprise52
 

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...
Comparing Teradata and Oracle Database, which product do you think is better and why?
I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...
Which companies use Teradata and who is it most suitable for?
Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...
Is Teradata a difficult solution to work with?
Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...
 

Comparisons

 

Also Known As

No data available
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture, Teradata Vantage Enterprise (DIY)
 

Overview

 

Sample Customers

Information Not Available
Netflix
Find out what your peers are saying about Teradata vs. dbt and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.