Oracle Big Data Appliance vs Teradata comparison

Oracle Big Data Appliance

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Executive SummaryUpdated on Apr 20, 2025

Teradata and Oracle Big Data Appliance compete in the big data analytics arena with Teradata having an edge in query performance, while Oracle offers a comprehensive feature set. Pricing and support favor Teradata, although Oracle's features may justify its higher cost for some buyers.

Features: Teradata provides high-speed data retrieval, powerful data warehousing, and excellent analytical functions. Oracle integrates well with the Oracle ecosystem, offers extensive analytics tools, and provides a seamless data processing environment.

Room for Improvement: Teradata could benefit from an enhanced interface and reduced complexity in query management. Improvements in cloud integration and cost transparency would be beneficial. Oracle might need to streamline its deployment process, improve user interface simplicity, and address the learning curve for new users.

Ease of Deployment and Customer Service: Teradata's deployment is straightforward, with strong customer support for smooth infrastructure integration. Oracle Big Data Appliance can be complex due to its extensive features, balanced by robust support services.

Pricing and ROI: Teradata generally has lower initial setup costs, resulting in a quicker ROI due to efficient performance. Oracle's potentially higher setup cost offers long-term value through capability and integration benefits, justifying its price for some.

To learn more, read our detailed Oracle Big Data Appliance vs. Teradata Report (Updated: April 2025).

Oracle Big Data Appliance 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

Oracle Big Data Appliance

Ranking in Data Warehouse

19th

Average Rating

8.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Data Warehouse

3rd

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of May 2025, in the Data Warehouse category, the mindshare of Oracle Big Data Appliance is 1.2%, down from 1.3% compared to the previous year. The mindshare of Teradata is 15.9%, up from 15.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Featured Reviews

Mohammed Hamad

AI & Data Engineering Lead at a tech services company with 10,001+ employees

Provides clean, centralized data

From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera. Oracle could also improve Big Data Appliance by having one technology on their stack and working on it instead of continually changing the name or technologies or features. In addition, they could have a program to enable their partners to use this technology because right now, I have to have an expert to use the AI elements.

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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

"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."

"This is a comprehensive solution that is easy to deploy."

"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."

"The product is reliable."

"We really enjoy the FastLoad, TPump, and MultiLoad features."

"There are several features of Teradata that I like. One of the most basic is the indexes. I also like that it provides lower TCO. It also has the optimizer feature which is a good feature and isn't found in other legacy systems. Parallelism is also another feature I like in Teradata because when you are running or hosting on multiple systems, you have this shared-nothing architecture that helps. Loading and unloading in Teradata are also really helpful compared to other systems."

"Teradata can be deployed on-premise, on the cloud, or in a virtual machine, which means customers can move without having to create their architecture all over again."

"The most valuable feature of Teradata is the quick processing of large data."

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

"The cloud is ten times better than physical hardware; it is more cost-effective and the upgrade process is ten times easier."

"Teradata's most valuable feature is that it's easy to use."

More Teradata pros

Cons

"The product should be simplified for the average user."

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."

"Teradata can improve the way it handles big data and unstructured data."

"I would like more security and speed."

"Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly."

"Teradata's pricing is quite high compared to Redshift, Synapse, or GCP alternatives."

"The cloud is the new challenge and the new opportunity."

"Teradata's UI could be improved."

"It would help to make scaling easier with a reduced cost. "

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

More Teradata cons

Pricing and Cost Advice

"Oracle's prices are too high compared to others in the market."

"Teradata is expensive but gives value for money, especially if you don't want to move your data to the cloud."

"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."

"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."

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

"It's a very expensive product."

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

"The cost is significantly high."

"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."

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

Financial Services Firm

31%

Computer Software Company

15%

Government

10%

University

Financial Services Firm

26%

Computer Software Company

10%

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

Data Warehouse

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Also Known As

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

Overview

Oracle Big Data Appliance is a flexible, high-performance, secure platform for running diverse workloads on Hadoop and NoSQL systems. With Oracle Big Data SQL, Oracle Big Data Appliance extends Oracle’s industry-leading implementation of SQL to Hadoop and NoSQL systems. By combining the newest technologies from the Hadoop ecosystem and powerful Oracle SQL capabilities together on a single pre-configured platform, Oracle Big Data Appliance is uniquely able to support rapid development of new Big Data applications and tight integration with existing relational data.

For more information on Oracle Big Data Appliance, visit Oracle.com

Oracle

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

Caixa Bank

Netflix

Oracle Big Data Appliance vs. Teradata