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Heavy.AI vs Teradata comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 5, 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

Heavy.AI
Ranking in Relational Databases Tools
24th
Average Rating
7.6
Reviews Sentiment
5.1
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Teradata
Ranking in Relational Databases Tools
7th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
83
Ranking in other categories
Customer Experience Management (5th), Backup and Recovery (11th), Data Integration (15th), Data Warehouse (2nd), BI (Business Intelligence) Tools (8th), Marketing Management (4th), Cloud Data Warehouse (2nd), Database Management Systems (DBMS) (5th)
 

Mindshare comparison

As of August 2026, in the Relational Databases Tools category, the mindshare of Heavy.AI is 0.7%, up from 0.2% compared to the previous year. The mindshare of Teradata is 3.9%, down from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Relational Databases Tools Mindshare Distribution
ProductMindshare (%)
Teradata3.9%
Heavy.AI0.7%
Other95.4%
Relational Databases Tools
 

Featured Reviews

reviewer2886843 - PeerSpot reviewer
Service Cloud Gb Strat High Technology Enterprise Account Executive at a tech vendor with 10,001+ employees
Interactive analytics has revealed territory gaps and now needs simpler, more conversational guidance
I think whenever you're using these tools, you want it to be as conversational as possible, and I think more of that would be helpful for Heavy.AI. Allowing you to ask questions on how to do things inside of Heavy.AI and have it actually show you how to do it as you're doing it would be beneficial. That way you don't have to spend a lot of time trying things out through trial and error. Trial and error can be helpful because you're learning it that way, but at the same time, when you're just trying to do things quickly and you're not a professional or a user that uses it all the time, you might not have that. So you want to be able to get that information quickly and easily. Some aspects I didn't like, but some of it's just like, "of course not." I wish I could snap my fingers and have everything be perfect, but that's not realistic. The infrastructure is probably fairly expensive. I can't afford to do that. I would need my business, the company that I work for to do it for us. Otherwise I can't really do it. It's just expensive. I did feel that it was pretty easy to use, but I'm a little bit more experienced than the average person, so maybe someone less technical like my colleagues would struggle initially to figure it out. I think maybe enhancing the user-friendliness for people that are not coders, just kind of setting up the workflows and things so it's just easier would help. It seems to be more purpose-built for spatial stuff, for location plus time and things, but general purpose BI is kind of an important thing. I don't think people were actually taking advantage of that, and when they're not doing that, it creates a little bit of trouble.
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

"Heavy.AI being able to do these things without having that background was powerful for me."
"We did see a saving of time and cost because we had a one-stop shop where we could access GPU utilization along with plotting of geographical data."
"I found all parts --loading, transformation, processing & querying work in parallel, and end-to-end-- to be valuable."
"The most valuable feature of Teradata is the quick processing of large data."
"Our customers are very happy with the configuration."
"It is the core of our fundamental real-time reporting and operational planning and has saved us over eight figures in the operational run costs, improved data quality and consistency as well as reduced our overall infrastructure support requirements."
"Performance-wise, Teradata beats everything."
"It is very stable. It's 100% uptime. Speed and resilience are one of the greatest features of this product. In almost twenty years we've never had downtime, except for outages for patches and upgrades. We've never had a system failure in twenty years."
"It's stable and reliable."
"We did performance testing. We had a set of real life MicroStrategy reports. Our conditions were: Not allowed to redesign data model, not allowed to rewrite the queries, all queries should be generated by MicroStrategy, no aggregates. Teradata appeared to be way faster than a similarly configured (in terms of hardware) Oracle server."
 

Cons

"Heavy.AI can be improved since it is a very large and comprehensive tool. For someone who does not have expertise in the tool, they will struggle somewhat, so I think it could be made easier for people."
"My experience with that was expensive to do for myself, so I had to get the company to sort of allow me to do it for Heavy.AI."
"There is some improvement required on OLTP level and some analytical function is missing."
"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."
"The only issue our company has with Teradata IntelliFlex is that it is not cost-effective because of the way the product has been designed."
"It's primarily designed for big projects and therefore, the pricing is pretty high. It's not suitable for smaller companies."
"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."
"Teradata's UI could be improved."
"However, adding additional space once your disks are full in the past was expensive."
"​The initial setup was complex as we had to rewrite a lot of the code.​"
 

Pricing and Cost Advice

Information not available
"​I would advise others to look into migration and setup as a fixed price and incorporate a SaaS option for other Teradata services​."
"It's a very expensive product."
"Teradata used to be expensive, but they have been lowering their prices."
"The solution requires a license."
"The cost is significantly high."
"The price of Teradata is on the higher side, and I think that it where they lose out on some of their business."
"Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions."
"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."
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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
Construction Company
35%
Insurance Company
19%
Healthcare Company
9%
Comms Service Provider
5%
Financial Services Firm
18%
Manufacturing Company
8%
Construction Company
8%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise13
Large Enterprise53
 

Questions from the Community

What needs improvement with Heavy.AI?
Heavy.AI can be improved since it is a very large and comprehensive tool. For someone who does not have expertise in the tool, they will struggle somewhat, so I think it could be made easier for pe...
What is your primary use case for Heavy.AI?
Heavy.AI is my main tool for large-scale data plotting and analysis. We have a lot of geographical data which we process for IoT vehicle fleets and cell tower pings. For this, we analyze and plot t...
What advice do you have for others considering Heavy.AI?
My advice to others looking into using Heavy.AI is to understand data and concepts in depth before using the tool rather than using it blindly. I give Heavy.AI a rating of 9.
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

OmniSci
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture, Teradata Vantage Enterprise (DIY)
 

Overview

 

Sample Customers

Pactriglo, TUTELA, Skyhook, npm, Inc., Simulmedia
Netflix
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