Own Data Platform vs Teradata comparison

Read 76 Teradata reviews

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87% willing to recommend

Own Data Platform

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Executive SummaryUpdated on Apr 20, 2025

Teradata and Own Data Platform are competing in the data management and analytics category. Teradata is favored for its strong analytical capabilities, while Own Data Platform stands out for its customization and integration options.

Features: Teradata offers scalable analytics which enable advanced data modeling and analysis. It is also known for robust data warehousing capabilities for large-scale data handling. Teradata provides a range of standardized offerings. Own Data Platform provides an adaptable architecture for seamless integration. Its customizable solutions cater to specific industry needs, offering greater flexibility. It allows unique tailored solutions for diverse applications.

Ease of Deployment and Customer Service: Teradata offers traditional deployment models with comprehensive support services ensuring reliable operation. Own Data Platform provides cloud-based deployment which enhances flexibility and scalability. Teradata has established customer service protocols for user assistance. Own Data Platform offers dedicated support to handle unique customer requirements efficiently.

Pricing and ROI: Teradata has high setup costs but delivers significant ROI through its robust analytical power in large implementations. Own Data Platform offers competitive pricing with flexible models, making it cost-effective especially for smaller organizations. Teradata's larger upfront cost is balanced by long-term insights potential, whereas Own Data Platform's lower initial investment yields quicker returns in various scenarios.

To learn more, read our detailed Own Data Platform vs. Teradata Report (Updated: April 2025).

Own Data Platform vs. Teradata

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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

Own Data Platform

Ranking in Backup and Recovery

37th

Average Rating

9.0

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Database Security (9th), SaaS Backup (12th), Application Testing Services (6th)

Teradata

Ranking in Backup and Recovery

20th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Data Integration (17th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of May 2025, in the Backup and Recovery category, the mindshare of Own Data Platform is 0.3%, up from 0.3% compared to the previous year. The mindshare of Teradata is 0.1%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Backup and Recovery

Featured Reviews

Divaker Singh

Salesforce Consultant at Girikon LLCGirikon

Efficient data management with robust restore feature and room for improved anonymization

We manage the customizing and seeding parts for our customers, using Own Data Platform to provide backup and recovery services. We work with exhibition companies that regularly expand their operations Own Data Platform provides a comprehensive backup and recovery solution, allowing us to manage…

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SurjitChoudhury

Data engineer at Cocos pt

Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities

We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

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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 valuable feature for our customers is the restore functionality."

"Building a data warehouse with Teradata has definitely helped a lot of our downstream applications to more easily access information."

"It's stable and reliable."

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

"IntelliFlex is easy to scale - one of its best features is that you can upscale it to the size you want."

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

"It's very mature from a technology perspective."

"Cuts time to process huge amounts of data with efficient analytical queries."

"It has massive parallel processing ability to do large amounts of concurrent querying."

More Teradata pros

Cons

"The anonymization feature can be improved."

"An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly."

"Teradata has a few AI models, but in data science, we need more flexibility."

"Data synchronization to the DR site."

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

"The initial setup is complex because there are a lot of factors that come into play, including the amount of software and applications that require access."

"If I want to implement an upgrade, I'd like to see how it will be different. Ideally, Data Lab should help me test production items and also do future things. Future releases should be downloadable and testable in Data Lab."

"There is some improvement required on OLTP level and some analytical function is missing."

"Stability-wise, we have had some issues with automation and the ability to handle large datasets."

More Teradata cons

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."

"The initial cost may seem high, but the TCO is low."

"The solution requires a license."

"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."

"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."

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

"Teradata is not cheap, but you get what you pay for."

"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."

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…

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Top Industries

By visitors reading reviews

Healthcare Company

10%

Financial Services Firm

10%

Insurance Company

Manufacturing Company

Financial Services Firm

26%

Computer Software Company

11%

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What is your experience regarding pricing and costs for Own Data Platform?

The pricing is somewhat high, rated at an eight out of ten. However, the value provided justifies the cost compared to other tools.

What needs improvement with Own Data Platform?

The anonymization feature can be improved. It’s currently not straightforward and often requires a technical person to operate, which can be challenging for non-technical users.

What is your primary use case for Own Data Platform?

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,...

Salesforce Backup and Restore vs Own Data Platform

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Compared 7% of the time

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Product Reports

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Also Known As

Own Data Archiving, Own Data Security, Own Data Seeding

IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture

Overview

OwnBackup offers administrators and developers peace of mind around SaaS data loss and corruption recovery. Our platform provides a comprehensive solution to backup, compare, recover, and manage large, complex SaaS-based data sets. With OwnBackup Sandbox Seeding, Development and QA teams can shorten cycles by configuring and replicating relevant test data sets to sandboxes, on demand, with just a few clicks.

Own

Teradata is a scalable data analytics platform designed to meet enterprise demands for large-scale data management and processing, focusing on performance, scalability, and security for complex query executions.

As a leading data warehousing solution, Teradata integrates advanced analytics enabling organizations to derive insights from massive datasets. It supports high-volume data workloads with its architecture optimized for analytical queries. Users benefit from its robust scalability, allowing seamless expansion as data grows. Teradata's SQL engine is compatible with a wide range of data types, ensuring flexibility in data analysis. With advanced security measures, it protects sensitive data across various environments, providing peace of mind to users handling critical information.

What are the most important features of Teradata?

Linear Scalability: Easily expands data processing capabilities to handle increasing data loads without performance degradation.
Advanced Analytics: Supports complex analytical operations integrating machine learning and AI for predictive insights.
SQL Compatibility: Offers a comprehensive SQL interface that supports complex queries across diverse data types.
Data Security: Implements rigorous security protocols to protect data integrity and confidentiality.

What benefits and ROI should users look for?

Improved Decision-Making: Derive actionable insights quickly for strategic business decisions.
Cost Efficiency: Optimized resource usage reduces operational costs associated with data processing.
Increased Productivity: Streamlined data operations save time, allowing teams to focus on analysis.
Enhanced Scalability: Seamless growth without significant additional investment as data volumes increase.

Teradata is widely used in industries like finance, telecommunications, and healthcare, where data-driven decisions are critical. Companies leverage its robust analytics capabilities to enhance customer experiences, streamline operations, and ensure compliance with regulatory requirements. In these sectors, quick access to data insights can significantly impact competitive advantage.

Sample Customers

Workiva, HR Owen, Tommy Bakama, Kanshoo, NTN, Athena Health, Interlochen Center for the Arts, Arizona State University, Pauley Financial

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Own Data Platform vs. Teradata