Teradata vs Upsolver comparison

Teradata and Upsolver are both solutions in the Data Integration category. Teradata is ranked #13 with an average rating of 7.7, while Upsolver is ranked #39 with an average rating of 8.3. Teradata holds a 0.9% mindshare in DI, compared to Upsolver’s 0.7% mindshare. Additionally, 88% of Teradata users are willing to recommend the solution, compared to 100% of Upsolver users who would recommend it.

Teradata

Read 83 Teradata reviews

11,786 Views
1,532 Comparison Views

88% willing to recommend

Upsolver

Read 3 Upsolver reviews

869 Views
704 Comparison Views

100% willing to recommend

Teradata

Upsolver

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 4, 2026

Teradata and Upsolver operate in the competitive data management space. While Teradata provides robust enterprise solutions, Upsolver has the upper hand with its flexibility and real-time data processing capabilities.

Features: Teradata is well-known for advanced analytics, scalability, and security features, suitable for large-scale data in complex environments. Upsolver shines with ease of integration, real-time processing capabilities, and support for diverse data formats. Teradata offers deep analytic capabilities, whereas Upsolver excels in adaptability and agility.

Ease of Deployment and Customer Service: Teradata's deployment is more intricate, requiring significant resources but backed by extensive customer service and training. Upsolver provides a simpler deployment experience with intuitive interfaces and comprehensive documentation, minimizing the need for extensive support. Teradata's strength lies in structured support, while Upsolver impresses with simplicity and quick setup.

Pricing and ROI: Teradata often involves higher initial costs due to its comprehensive infrastructure but delivers substantial ROI through deep analytical capabilities. Upsolver offers a more cost-effective pricing model and significant ROI by reducing time-to-insight and operational costs. Teradata demands a heavier upfront investment, while Upsolver presents an agile and cost-effective solution for businesses seeking rapid data insights.

To learn more, read our detailed Teradata vs. Upsolver Report (Updated: March 2026).

Buyer's Guide

Teradata vs. Upsolver

March 2026

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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

Teradata

Ranking in Data Integration

13th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

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)

Upsolver

Ranking in Data Integration

39th

Average Rating

8.4

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Streaming Analytics (21st)

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Teradata is 0.9%, up from 0.9% 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
Product	Mindshare (%)
Teradata	0.9%
Upsolver	0.7%
Other	98.4%

Data Integration

Featured Reviews

David Durand Velásquez

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.

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reviewer2784462

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.

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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 most important thing we get out of the product is the intelligence that we derive."

"In Data Lab, you can schedule any testing you want to do in production, take a small subset of data from production, copy it there, and run all your tests, which reduces your testing costs because it's all in the lab."

"The most valuable features are the large volume of data and the structuring of the data to optimize it and get very optimal data warehouse solutions for customers."

"Our customers are very impressed by Teradata's speed, because it's massively parallel processed."

"Teradata is great as far as scalability once you have the product."

"Auto-partitioning and indexing, and resource allocation on the fly are key features."

"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."

More Teradata pros

"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."

"Customer service is excellent, and I would rate it between eight point five to nine out of ten."

"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."

Cons

"Since I was working on the very basic, legacy systems, the memory thing was always a challenge."

"I would like more security and speed."

"I choose 8 out of 10 for Teradata because there is always the scope for improvement."

"Their level of technical support is adequate. It could be better."

"There are a few things where you are totally dependent on the customer service and support from Teradata. This is an area where they really need to improve a bit, especially when you're talking about cloud service integration."

"I think the UI is not there yet. It could be improved by being more user-friendly."

"They should add more connectors to different platforms."

"It should be compatible and free on CLOUD/ AWS. Currently many DB's on AWS are free, Teradata is also on Amazon Web Services, but its charged and no documentation available to practice those LABS."

More Teradata cons

"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."

"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."

"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."

"There is room for improvement in query tuning."

Pricing and Cost Advice

"Teradata used to be expensive, but they have been lowering their prices."

"I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive."

"We had a lot of parties involved when purchasing from the AWS Marketplace. They are very flexible and aggressive in trying to close the deal. They are good at what they have to offer and listening to the customer. It's a two-way street."

"Price is quite high, so if it is really possible to use other solutions (e.g. you do not have strict requirements for performance and huge data volumes), it might be better to look at alternatives from the RDBMS world."

"Teradata is a very expensive solution."

"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."

"The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing."

"Make sure you have the in-house skills to design and support the solution, as relying on external sources is extremely costly and tends to lock you into specific platforms, tools, and paradigms."

More Teradata pricing and cost advice

"Upsolver is affordable at approximately $225 per terabyte per year."

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Comparison Review

it_user232068

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…

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Manufacturing Company

Computer Software Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	13
Large Enterprise	52

No data available

Questions from the Community

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...

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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...

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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,...

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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, ...

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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...

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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...

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Comparisons

Snowflake vs Teradata

Compared 5% of the time

Oracle Database vs Teradata

Compared 5% of the time

SQL Server vs Teradata

Compared 4% of the time

Oracle Exadata vs Teradata

Compared 4% of the time

IBM Db2 Database vs Teradata

Compared 3% of the time

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Databricks vs Upsolver

Compared 12% of the time

SAS Access vs Upsolver

Compared 9% of the time

Alteryx Designer vs Upsolver

Compared 9% of the time

IBM Cloud Pak for Data vs Upsolver

Compared 8% of the time

Striim vs Upsolver

Compared 8% of the time

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Product Reports

Buyer's Guide

Teradata

March 2026

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Buyer's Guide

Data Integration

March 2026

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Also Known As

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

No data available

Overview

Teradata is a powerful tool for handling substantial data volumes with its parallel processing architecture, supporting both cloud and on-premise environments efficiently. It offers impressive capabilities for fast query processing, data integration, and real-time reporting, making it suitable for diverse industrial applications.

Known for its robust parallel processing capabilities, Teradata effectively manages large datasets and provides adaptable deployment across cloud and on-premise setups. It enhances performance and scalability with features like advanced query tuning, workload management, and strong security. Users appreciate its ease of use and automation features which support real-time data reporting. The optimizer and intelligent partitioning help improve query speed and efficiency, while multi-temperature data management optimizes data handling.

What are the key features of Teradata?

Parallel Processing Architecture: Enables efficient handling of substantial data volumes.
Cloud and On-Premise Deployment: Offers seamless adaptability across environments.
Query Tuning: Improves speed and performance of data retrieval processes.
Workload Management: Ensures optimal resource allocation for enhanced performance.
Robust Security: Provides high levels of data protection and system integrity.
Data Integration: Facilitates cohesive data management from multiple sources.
Automation for Real-time Reporting: Enhances timely data insights and decision-making.
Optimizer and Intelligent Partitioning: Further increase query speed and system efficiency.
Multi-Temperature Data Management: Optimizes the handling and retrieval of data.

What benefits and ROI do users look for?

Efficient Data Management: Facilitates smooth integration and processing of diverse data sets.
Scalability: Easy adjustment to increasing or decreasing data requirements.
Improved Performance: Fast query speeds and optimized resource use.
Comprehensive Security: Safeguards data integrity and accessibility.
Ease of Use: Simplifies data handling and operational processes.

In the finance, retail, and government sectors, Teradata is employed for data warehousing, business intelligence, and analytical processing. It handles vast datasets for activities like customer behavior modeling and enterprise data integration. Supporting efficient reporting and analytics, Teradata enhances data storage and processing, whether deployed on-premise or on cloud platforms.

Teradata

Upsolver's mission is to turn engineering-intensive data lakes into easy-to-use repositories that serve 50X more data professionals compared to the status-quo today. Upsolver cuts 95% from the tedious process of preparing event data for analytics and machine learning, using a visual SQL-based interface, a cloud-native data platform and deep technology for stream-processing, indexing and eventually-consistent file systems.

Upsolver

Sample Customers

Netflix

Information Not Available

Buyer's Guide

Teradata vs. Upsolver

March 2026

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