IBM Cloud Pak for Data vs Teradata comparison

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IBM Cloud Pak for Data

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Executive SummaryUpdated on Jan 4, 2026

Teradata and IBM Cloud Pak for Data compete in the data management and analytics category. Teradata is noted for its speed and performance, while Cloud Pak is preferred for AI integration and data governance.

Features: Teradata offers fast query execution with massively parallel processing and a shared-nothing architecture, allowing efficient handling of large data volumes. Its workload management options and query tuning capabilities further enhance performance. Cloud Pak for Data delivers strong AI and machine learning features with Watson Studio and Watson Knowledge Catalog, enabling seamless data governance and AI-driven insights. Its diverse data management integrations facilitate better adaptability across multiple data sources.

Room for Improvement: Teradata could improve in cloud service offerings, pricing flexibility, and user interface design. Enhancing compatibility with big data platforms is also required. Cloud Pak for Data seeks improved seamless cloud integration with third-party providers. Enhanced user experience to minimize delays and optimize cloud connectivity would benefit users.

Ease of Deployment and Customer Service: Teradata provides flexible deployment options from on-premises to hybrid and cloud environments, with generally positive feedback on its reliable technical support and customer service. IBM Cloud Pak for Data offers similar deployment flexibility but needs to improve deployment processes and administrative functions. Both platforms are noted for responsive customer service, though Teradata edges slightly higher in addressing user concerns effectively.

Pricing and ROI: Teradata's premium pricing reflects its robust performance and extensive features, providing excellent ROI for large-scale implementations. It introduces flexible pricing models to counter initial costs. Cloud Pak for Data also has high pricing but emphasizes value through its comprehensive AI and data management tools. While both are deemed expensive, Teradata is valued for efficient time and resource savings, whereas Cloud Pak's cost-effectiveness is debated relative to its feature set.

To learn more, read our detailed IBM Cloud Pak for Data vs. Teradata Report (Updated: December 2025).

IBM Cloud Pak for Data 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:

ROI

Sentiment score

6.5

IBM Cloud Pak for Data helps large enterprises improve data quality, boosting AI processes and enhancing decision-making productivity.

Sentiment score

6.9

Teradata significantly boosts speed, efficiency, and ROI, with studies showing a 427% average ROI over three years.

We have been able to drive responsible, transparent, and explainable AI workflow to operationalize AI and mitigate risk and regulatory compliance easily.

For more quotes and insights, download the IBM Cloud Pak for Data report

Senior Data Analyst at Wipro

At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.

Shugoyal Shugoyal

Senior product analyst at a financial services firm with 10,001+ employees

Independent research showed that Teradata VantageCloud users achieved an average ROI of 427% across three years with payback under a year, demonstrating the platform's ability to deliver a strong financial return.

Engineers at a consultancy with 11-50 employees

We have realized a return on investment, with a reduction of staff from 27 to eight, and our current return on investment is approximately 14%.

For more quotes and insights, download the Teradata report

Interim and Fractional CIO and CTO at a consultancy with 11-50 employees

Customer Service

Sentiment score

7.7

IBM Cloud Pak for Data's support is responsive and available 24/7, despite some delays due to system complexity.

Sentiment score

7.1

Teradata's support is praised for professionalism and responsiveness, but feedback on speed is mixed; training resources enhance service.

Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.

Data asset management engineer at a tech services company with 1-10 employees

I would rate IBM's support at about a seven or eight out of ten because we have good support coverage owing to our long association with IBM.

reviewer2648136

EDW Manager at a university with 1,001-5,000 employees

Customer support should be more responsive and reach and respond on time.

For more quotes and insights, download the IBM Cloud Pak for Data report

Senior Data Analyst at Wipro

The customer support for Teradata has been great.

Interim and Fractional CIO and CTO at a consultancy with 11-50 employees

They are responsive and knowledgeable, and the documentation is very helpful.

Engineers at a consultancy with 11-50 employees

Customer support is very good, rated eight out of ten under our essential agreement.

For more quotes and insights, download the Teradata report

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

Scalability Issues

Sentiment score

7.4

IBM Cloud Pak for Data is praised for impressive scalability and compatibility, despite being resource-intensive, with ratings mostly 8-10.

Sentiment score

7.5

Teradata offers scalable cloud and on-premise solutions with strong adaptability, overcoming hardware limitations and cost challenges efficiently.

I have not noticed any downtime or lagging, especially when dealing with large data, so it is relatively very scalable.

For more quotes and insights, download the IBM Cloud Pak for Data report

Senior Data Analyst at Wipro

Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well.

Shugoyal Shugoyal

Senior product analyst at a financial services firm with 10,001+ employees

This flexibility allows organizations to scale according to their needs, balancing performance, cost, and compliance requirements.

For more quotes and insights, download the Teradata report

Engineers at a consultancy with 11-50 employees

This expansion can occur without incurring downtime or taking systems offline.

RajeshKumar25

Principal Consultant & Director at Quensulting

Stability Issues

Sentiment score

7.5

IBM Cloud Pak for Data is generally stable and well-rated, with users emphasizing scalability despite minor tool integration concerns.

Sentiment score

8.3

Teradata's robust architecture ensures exceptional stability and reliability, with minimal downtime and high user ratings despite some integration challenges.

No quotes available

For more quotes and insights, download the IBM Cloud Pak for Data report

Its massively parallel process architecture allows the platform to distribute workload efficiently, enabling organizations to run heavy analytic queries without compromising speed or stability.

Engineers at a consultancy with 11-50 employees

I find the stability to be almost a ten out of ten.

For more quotes and insights, download the Teradata report

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

The workload management and software maturity provide a reliable system.

RajeshKumar25

Principal Consultant & Director at Quensulting

Room For Improvement

IBM Cloud Pak for Data needs better integration, support, features, and pricing to attract small businesses and simplify adoption.

Teradata requires improvements in transaction processing, scalability, UI, cost-effectiveness, analytics features, integration capabilities, and security measures.

Setting up the hybrid and multi-cloud environments is a long job and it takes time.

Senior Data Analyst at Wipro

I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in.

For more quotes and insights, download the IBM Cloud Pak for Data report

Data asset management engineer at a tech services company with 1-10 employees

I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.

reviewer2648136

EDW Manager at a university with 1,001-5,000 employees

I want to highlight two features for improvement: first, storing data in various formats without requiring a tabular structure, accommodating unstructured data; and second, adding AI ML features to better integrate Gen AI, LLM concepts, and user-friendly experiences such as text-to-SQL capabilities.

Ganesh Verma

Data Engineer at Tredence Inc.

Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.

For more quotes and insights, download the Teradata report

Interim and Fractional CIO and CTO at a consultancy with 11-50 employees

Setup Cost

IBM Cloud Pak for Data's high pricing and complexity make it more suitable for large enterprises than smaller companies.

Teradata offers high-value analytics with flexible pricing, excelling in performance and ROI, ideal for large enterprises and data-intensive sectors.

The setup cost is very expensive.

Data asset management engineer at a tech services company with 1-10 employees

Regarding my experience with pricing, setup cost, and licensing, for a small organization, the price might be relatively high, but for huge enterprises such as ours, the price is relatively affordable.

For more quotes and insights, download the IBM Cloud Pak for Data report

Senior Data Analyst at Wipro

Teradata is much more expensive than SQL, which is well-performed and cheaper.

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.

RajeshKumar25

Principal Consultant & Director at Quensulting

Role-based access control (RBAC), strong audit and compliance features, high availability, fault tolerance, and encrypted data at rest and in-transit are key features.

For more quotes and insights, download the Teradata report

Engineers at a consultancy with 11-50 employees

Valuable Features

IBM Cloud Pak for Data excels with data virtualization, low-code navigation, robust security, and efficient data integration and collaboration.

Teradata excels in parallel processing, scalability, and performance, offering robust data management, security, and integration for efficient data warehousing.

From there, I can work my way into a more granular level, applying all of that information on top of my actual data to understand what my data looks like, where it came from, and where it went wrong, managing it throughout the cycle.

Data asset management engineer at a tech services company with 1-10 employees

The benefits of choosing IBM Cognos, in addition to saving on cost, include having institutional knowledge about maintaining this infrastructure and enough people who have developed on Cognos in the past, which creates comfort in its use.

reviewer2648136

EDW Manager at a university with 1,001-5,000 employees

We have been able to save approximately 80 percent of our time. We are not doing data analysis manually, so this relieves our data department of dealing with data.

For more quotes and insights, download the IBM Cloud Pak for Data report

Senior Data Analyst at Wipro

Teradata's security helps our organization meet compliance requirements such as GDPR and IFRS, and it is particularly essential for revenue contracting or revenue recognition.

Interim and Fractional CIO and CTO at a consultancy with 11-50 employees

Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments.

For more quotes and insights, download the Teradata report

Engineers at a consultancy with 11-50 employees

It facilitates data integration, where we integrate and analyze data from various sources, making it a powerful and high-quality reliable solution for the company.

reviewer2783274

Senior Data Engineer at a media company with 1,001-5,000 employees

Categories and Ranking

IBM Cloud Pak for Data

Ranking in Data Integration

23rd

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Teradata

Ranking in Data Integration

15th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (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 Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.3%, down from 1.6% compared to the previous year. The mindshare of Teradata is 0.9%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Teradata	0.9%
IBM Cloud Pak for Data	1.3%
Other	97.8%

Data Integration

Featured Reviews

Starts strong with data management capabilities but needs a demo database

Data asset management engineer at a tech services company with 1-10 employees

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

Read full review

Delivers consistent performance and enables advanced analytics across complex data environments

Engineers at a consultancy with 11-50 employees

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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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

26%

Manufacturing Company

10%

Computer Software Company

Government

Financial Services Firm

24%

Manufacturing Company

Computer Software Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	7
Large Enterprise	12

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

Questions from the Community

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

The pricing and setup cost are handled by a different procurement team. Our IT procurement team is centralized, so licensing and the actual cost of the software are taken care of by a different tea...

What needs improvement with IBM Cloud Pak for Data?

I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.

What is your primary use case for IBM Cloud Pak for Data?

The main use case for IBM Cognos is for business intelligence and reporting.

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,...

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

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Compared 7% of the time

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Compared 5% of the time

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Product Reports

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IBM Cloud Pak for Data

January 2026

Download Teradata product report

January 2026

Also Known As

Cloud Pak for Data

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

Overview

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

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.

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

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