Teradata vs Upsolver comparison

Teradata and Upsolver are both solutions in the Data Integration category. Teradata is ranked #15 with an average rating of 8.3, while Upsolver is ranked #39 with an average rating of 8.5. Teradata holds a 1.1% 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

20,701 Views
3,105 Comparison Views

88% willing to recommend

Upsolver

Read 4 Upsolver reviews

2,013 Views
1,610 Comparison Views

100% willing to recommend

Teradata

Upsolver

Comparison Buyer's Guide

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Executive SummaryUpdated on Apr 5, 2026

Teradata and Upsolver are competing products in the data management sector. Upsolver appears to have the upper hand with its advanced features and seamless cloud integration that many find worth the investment.

Features: Teradata is known for its robust analytics capacity, scalability across large enterprises, and strong pricing and support. Upsolver offers real-time analytics, simple event stream processing, and the ability to integrate with various cloud environments.

Ease of Deployment and Customer Service: Teradata demands extensive setup and specialized expertise for deployment. Its comprehensive customer service is essential for handling complex implementations. Upsolver provides a straightforward deployment process with focus on cloud-native architecture, offering efficient customer service tailored to its simpler integration.

Pricing and ROI: Teradata incurs substantial setup costs due to enterprise-level infrastructure requirements, resulting in slower ROI as necessary resources are invested. Upsolver presents a cost-effective entry point with faster ROI potential through its flexible pricing structure and reduced initial investment.

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

Buyer's Guide

Teradata vs. Upsolver

August 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

15th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Customer Experience Management (5th), Backup and Recovery (11th), Relational Databases Tools (7th), Data Warehouse (2nd), BI (Business Intelligence) Tools (8th), Marketing Management (4th), Cloud Data Warehouse (2nd), Database Management Systems (DBMS) (5th)

Upsolver

Ranking in Data Integration

39th

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Streaming Analytics (21st)

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Teradata is 1.1%, down from 1.1% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Teradata	1.1%
Upsolver	0.7%
Other	98.2%

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

"It has a solid set of tools and consulting services."

"Teradata has allowed us to provide an online BI solution that no other player was able to do."

"The most valuable feature is the ease of uploading data from multiple sources."

"Performance-wise, Teradata beats everything."

"The feature that we find most valuable is its ability to perform Massive Parallel Processing."

"Teradata solutions help organizations reduce IT, operations, and maintenance costs; enhance on-time delivery of products and services."

"It handles large amounts of information with a linear performance increase, in relation to a HW investment."

"We moved from an Enterprise platform, to non-Enterprise and ended up with a machine that was 20X more powerful."

More Teradata pros

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

"I have saved 50 to 60% on maintaining pipelines since using Upsolver."

"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."

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

"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."

Cons

"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."

"The initial setup was complex as we had to rewrite a lot of the code."

"I would like more security and speed."

"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."

"The SQL Assistant is very basic. This tool can be improved for usability."

"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."

"I would not say it was very performance efficient, but it was definitely good."

"My experience was the Teradata Solution Architects were less friendly and hid information and charged for simple things."

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 would say Upsolver's scalability is eight out of 10 because of pricing."

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

"There is room for improvement in query tuning."

"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."

Pricing and Cost Advice

"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."

"The price of the solution could be reduced, it is expensive."

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

"When looking into implementing this product, pricing is the main issue followed by technical expertise."

"The price of Teradata is on the higher side, and I think that it where they lose out on some of their business."

"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."

"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."

"I would advise others to look into migration and setup as a fixed price and incorporate a SaaS option for other Teradata services."

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

18%

Manufacturing Company

Construction Company

Comms Service Provider

Real Estate/Law Firm

14%

Manufacturing Company

14%

Retailer

12%

Construction Company

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	13
Large Enterprise	53

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 is that the pricing is nine out of 10.

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What needs improvement with Upsolver?

I think Upsolver can be improved with deeper integration with external orchestration out of the box. I would appreciate more clear dashboards with billing in real time as a needed improvement.

See all answers

What is your primary use case for Upsolver?

My main use case for Upsolver is to operate with changes in the structure of new data without a pipeline disrupting. I write SQL queries in Upsolver, and the platform takes care of the data itself,...

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Comparisons

Snowflake vs Teradata

Compared 4% of the time

Oracle Database vs Teradata

Compared 3% of the time

SQL Server vs Teradata

Compared 3% of the time

Databricks vs Teradata

Compared 3% of the time

MySQL vs Teradata

Compared 2% of the time

More Teradata Competitors

Databricks vs Upsolver

Compared 11% of the time

Striim vs Upsolver

Compared 11% of the time

Rivery vs Upsolver

Compared 7% of the time

SAS Access vs Upsolver

Compared 7% of the time

Alteryx Designer vs Upsolver

Compared 7% of the time

More Upsolver Competitors

Product Reports

Buyer's Guide

Teradata

July 2026

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Buyer's Guide

Data Integration

August 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 offers a data lakehouse platform that simplifies big data processing and analytics, enabling data teams to efficiently handle large-scale datasets.

Upsolver's platform focuses on simplifying the complexities of data engineering by transforming raw data into queryable formats quickly. It allows seamless integration with cloud storage and various database systems, providing flexibility for data-driven businesses. The platform automates data preparation tasks, reducing manual coding and allowing teams to focus on extracting insights. Its scalable architecture supports real-time analytics and batch processing.

What are the key features of Upsolver?

Data Ingestion: Easily ingest data from multiple sources with minimal configuration.
Schema On-Read: Automatically interpret data schemas, simplifying data management.
Streaming SQL: Transform and analyze streaming data using a familiar SQL syntax.
Data Lake Integration: Seamlessly connect with data lakes for streamlined workflows.

What benefits and ROI should users consider?

Time Savings: Faster data processing reduces time to insights.
Cost Efficiency: Scalable architecture optimizes infrastructure costs.
Scalability: Handle growing data volumes effortlessly.
Flexibility: Supports wide data storage and processing strategies.

In the e-commerce industry, Upsolver helps businesses optimize their data pipelines for better customer segmentation and personalization, while in finance, it enhances fraud detection capabilities through real-time data analytics.

Upsolver

Sample Customers

Netflix

Information Not Available

Buyer's Guide

Teradata vs. Upsolver

August 2026

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