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Oracle Big Data Appliance vs Teradata comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 20, 2025

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
5
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
76
Ranking in other categories
Customer Experience Management (6th), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (8th), 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 - PeerSpot reviewer
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.
SurjitChoudhury - PeerSpot reviewer
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.

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 data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems."
"It effectively has allowed us to remove over 20 portion copies of the data sets on other DB platforms for real-time operational reporting purposes."
"It is very stable. It's 100% uptime. Speed and resilience are one of the greatest features of this product. In almost twenty years we've never had downtime, except for outages for patches and upgrades. We've never had a system failure in twenty years."
"The most valuable features of Teradata are that it is a massively parallel platform and I can receive a lot of data and get the queries out correctly, especially if it's been appropriately designed. The native features make it very suitable for multiple large data tasks in a structured data environment. Additionally, the automation is very good."
"Teradata has good performance, the response times are very fast. Overall the solution is easy to use. When we do the transformation, we have all of our staging and aggregation data available."
"The tool's most valuable feature is the warehousing model."
"I've never had any issues with scalability."
"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."
 

Cons

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
"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."
"There is some improvement required on OLTP level and some analytical function is missing."
"Teradata is an old data warehouse, and they're not improving in terms of new, innovative features."
"It could use some more advanced analytics relating to structured and semi-structured data."
"The solution needs improvement in its stability, support and pricing."
"The reporting side wasn't very good in the past, but with the latest versions, it's getting better. Still, the friendliness of the PDC reporting and functionality needs to 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."
"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 like to see an improved Knowledge Base on the web."
 

Pricing and Cost Advice

"Oracle's prices are too high compared to others in the market."
"The solution requires a license."
"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."
"The cost of running Teradata is quite high, but you get a good return on investment."
"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."
"​I would advise others to look into migration and setup as a fixed price and incorporate a SaaS option for other Teradata services​."
"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."
"The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000."
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Comparison Review

it_user232068 - PeerSpot reviewer
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…
 

Top Industries

By visitors reading reviews
Financial Services Firm
30%
Computer Software Company
16%
Government
11%
University
8%
Financial Services Firm
26%
Computer Software Company
11%
Healthcare Company
7%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Ask a question
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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...
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,...
 

Also Known As

No data available
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture
 

Overview

 

Sample Customers

Caixa Bank
Netflix
Find out what your peers are saying about Oracle Big Data Appliance vs. Teradata and other solutions. Updated: May 2025.
851,604 professionals have used our research since 2012.