Quantum DXi Series vs Teradata comparison

Quantum and Teradata are both solutions in the Backup and Recovery category. Quantum is ranked #65, while Teradata is ranked #15 with an average rating of 7.7. Quantum holds a 0.7% mindshare in BRS, compared to Teradata’s 0.5% mindshare. Additionally, 66% of Quantum users are willing to recommend the solution, compared to 88% of Teradata users who would recommend it.

Quantum DXi Series

Read 2 Quantum DXi Series reviews

1,546 Views
835 Comparison Views

66% willing to recommend

Teradata

Read 83 Teradata reviews

10,773 Views
646 Comparison Views

88% willing to recommend

Quantum DXi Series

Teradata

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 4, 2026

Teradata and Quantum DXi Series are competing in data management and storage. Quantum DXi Series has the upper hand due to its advanced features despite a higher price.

Features: Teradata provides data analytics, scalability, and robust data warehousing for large enterprises. Quantum DXi Series offers data protection, backup, and features like deduplication and replication, emphasizing data security and storage efficiency.

Ease of Deployment and Customer Service: Teradata is known for straightforward deployment and comprehensive support, aiding in easy implementation and operation for businesses. Quantum DXi Series, while needing specialized deployment, excels with detailed customer service, offering an edge in complex environments.

Pricing and ROI: Teradata features a competitive pricing structure, providing quicker ROI for extensive analytics needs. Quantum DXi Series carries higher initial costs, but its specialized features deliver long-term ROI through data security and optimization. The choice relies on prioritizing cost efficiency and analytics or advanced storage and security features.

To learn more, read our detailed Quantum DXi Series vs. Teradata Report (Updated: December 2025).

Buyer's Guide

Quantum DXi Series vs. Teradata

December 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

Quantum DXi Series

Ranking in Backup and Recovery

65th

Average Rating

9.6

Reviews Sentiment

7.7

Number of Reviews

Ranking in other categories

Deduplication Software (12th)

Teradata

Ranking in Backup and Recovery

15th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Data Integration (15th), Relational Databases Tools (6th), Data Warehouse (3rd), BI (Business Intelligence) Tools (8th), Marketing Management (5th), Cloud Data Warehouse (3rd), Database Management Systems (DBMS) (3rd)

Mindshare comparison

As of January 2026, in the Backup and Recovery category, the mindshare of Quantum DXi Series is 0.7%, up from 0.2% compared to the previous year. The mindshare of Teradata is 0.5%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Backup and Recovery Market Share Distribution
Product	Market Share (%)
Teradata	0.5%
Quantum DXi Series	0.7%
Other	98.8%

Backup and Recovery

Featured Reviews

reviewer2301564

Expert Backup at a tech services company with 201-500 employees

A virtual deduplication backup appliance that protects physical and virtual data across remote sites, the datacenter and cloud deployments

Given its ease of use and management, I believe there are no specific caveats that users need to be aware of during the setup of DXRIS for backups. The process was straightforward, and I did not encounter any challenges or issues. As for a rating on a scale of one to ten, with one being the worst and ten being the best, I would rate the Quantum DXI Series a nine. My deduction is primarily influenced by personal preferences, particularly regarding the user interface and it is a highly commendable system, I would rate it a solid nine out of ten.

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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.

Read full review

Quotes from Members

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

Pros

"While the challenges posed by the difficulties were significant, they prompted the replacement of problematic components, resulting in the resolution of issues. Importantly, there were no substantial ongoing concerns. Regarding the overall performance, it has been consistently excellent."

"I am impressed with the tool's technical alliance with Veeam and Veritas."

"The solution scales well on the cloud."

"Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running."

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

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

"The initial setup was straightforward."

"Teradata has immensely helped our organization to fetch the data at a faster rate, which has saved us quite a lot of time."

"Improved performance of ETL procedures, reporting."

"Their extensive experience in data warehousing, the platform's performance, and their strong reputation in the market are the most valuable."

More Teradata pros

Cons

"The product needs to improve performance while scaling out. It also needs to improve stability."

"Perhaps the most notable area for enhancement lies in the web interface for management. The current limitations in LDAP editing capabilities are not addressed in the UI, and I haven't observed any recent updates. It's possible that the new version of the DXI service incorporates improvements in the GUI, but I cannot confirm. While there is room for improvement in the current GUI, it remains a relatively minor issue. Overall, the system is comprehensive, covering aspects such as reports on latency and networking, leaving little room for additional enhancements in those areas."

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

"It's primarily designed for big projects and therefore, the pricing is pretty high. It's not suitable for smaller companies."

"Teradata is a bit late for the cloud."

"The current operational approach needs improvement."

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

"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 should focus on functionality for building predictive models because, in that regard, it can definitely improve."

"The increasing volumes of data demand more and more performance."

More Teradata cons

Pricing and Cost Advice

"I do not oversee this aspect, as pricing is contingent on factors such as volume, technical specifications, and the desired features. Consequently, I lack information on the pricing details and structure."

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

"The product cost is high for what the client gets. There may be more cost-effective solutions for small and medium-sized organizations."

"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."

"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."

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

"The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000."

"I am using the free version of Teradata."

"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."

More Teradata pricing and cost advice

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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…

Read full review

Top Industries

By visitors reading reviews

Financial Services Firm

25%

Computer Software Company

12%

Manufacturing Company

Retailer

Financial Services Firm

24%

Manufacturing Company

Computer Software Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Questions from the Community

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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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Product Reports

Buyer's Guide

Backup and Recovery

January 2026

Download Quantum DXi Series product report

Buyer's Guide

Teradata

January 2026

Download Teradata product report

Also Known As

DXi Series, Quantum DX

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

Overview

Quantum's DXi series deduplication solutions provides patented variable-length deduplication that not only reduces disk usage and capital expenditures, but also enables efficient data movement across the WAN to other sites and to the cloud.

Quantum

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

Sample Customers

Nihon Unisys, Nikoyo China

Netflix

Buyer's Guide

Quantum DXi Series vs. Teradata

December 2025

Free Report: Quantum DXi Series vs. Teradata

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