Apache Hadoop vs Oracle Big Data Appliance vs Teradata comparison

Oracle Big Data Appliance

Read 83 Teradata reviews

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Apache Hadoop

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Executive Summary

We performed a comparison between Apache Hadoop, Oracle Big Data Appliance, and Teradata based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse.

To learn more, read our detailed Data Warehouse Report (Updated: March 2026).

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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:

Mindshare comparison

As of April 2026, in the Data Warehouse category, the mindshare of Apache Hadoop is 3.7%, down from 4.3% compared to the previous year. The mindshare of Oracle Big Data Appliance is 2.5%, up from 0.9% compared to the previous year. The mindshare of Teradata is 9.0%, down from 15.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Teradata	9.0%
Apache Hadoop	3.7%
Oracle Big Data Appliance	2.5%
Other	84.8%

Data Warehouse

Featured Reviews

Nick Rapoport

Financial Advisor at a financial services firm with 10,001+ employees

Reliable performance maintained but requires ongoing management and support

Hadoop was used for years, but there were problems since the people who originally set it up left the firm. The group that owned it later didn't have the technical resources to properly maintain it. Although there was nothing wrong with Hadoop itself, issues arose without proper management and upgrades.

Platinum partnership leverages advanced storage and fosters seamless data integration

reviewer1031826

Analytics Lead at a tech vendor with 10,001+ employees

Areas of Oracle Big Data Appliance that can be improved include the pricing perspective because nowadays they have competition. We have so many technologies that have come to the market for less than even one-fourth or one-fifth of the Oracle price. For my side, the last time I worked with Oracle was in '21, '22. The price is a challenge that they have to look after. From the storage and data management perspective, I cannot recall anything that they have to improve, but they have to improve the visualization part significantly because they offer Oracle BI, which is an extremely not-matured application.

Delivers consistent performance and enables advanced analytics across complex data environments

David Durand Velásquez

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.

More Oracle Big Data Appliance pros

Quotes from Members

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

Pros

"Because we're able to process in parallel, we don't have to wait for the big data warehouse engine, we process down what the data is and then build it up to an answer, and we can have an answer in an hour rather than 10 hours."

"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics."

"Hadoop can store any kind of data—structured, unstructured, and semi-structured—and presents it using the relational model through Hive."

"What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution."

"It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."

"Real-time streaming and integration using Spark streaming and the ecosystem of Spark technologies inside Hadoop."

"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."

"What comes with the standard setup is what we mostly use, but Ambari is the most important."

More Apache Hadoop pros

"Big Data responds to my needs."

"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."

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

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

"We could work on large unstructured datasets from different parts of the world on Facebook and Twitter to get better insights."

"The best feature of Oracle Big Data Appliance, from a price perspective for the storage, is because they have technology called the ZFS technology; it offers huge storage with a decent price."

"The most valuable feature is that it can be used in conjunction with Spark memory processing, and our processing time has gone to 20 minutes from what used to be two or three hours on the mainframe."

"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."

"The product's scalability is great. Scalability-wise, I rate the solution a ten out of ten."

"BTEQ is the best feature of Teradata, as it allows me to execute multiple queries such as select, insert, update, and delete in a single script, handle errors, automate running multiple SQL statements, and schedule ETL jobs, making it lightweight and scriptable, unlike SQL Assistant."

"Teradata effectively uses parallelism to the granular level, performing better than other databases."

"There are two very useful features: one is the fast data input for more or less any online data, and two, it also has a lot of tools for data engineering or data manipulation that are compatible."

"It has reduced a lot of reworking on maintaining indexes, partitions, etc."

"Teradata's scalability is one of its best features."

"Performance-wise, Teradata beats everything."

More Teradata pros

Cons

"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, and if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."

"It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it."

"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."

"The upgrade path should be improved because it is not as easy as it should be."

"The solution is very expensive."

"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."

"It would be good to have more advanced analytics tools."

More Apache Hadoop cons

"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."

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

"We need to display the results on our website. I think there is another product that joins with it to give you the possibility."

"We had to pursue several performance tuning measures to bring up the system to scale."

"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."

"However, adding additional space once your disks are full in the past was expensive."

"If I want to implement an upgrade, I'd like to see how it will be different."

"It could use some more advanced analytics relating to structured and semi-structured data."

"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."

"The usability could be a bit better. It could be a bit more user-friendly."

"The primary challenge with Teradata lies in its cost structure, encompassing subscription fees, software licenses, and hardware expenses."

"The solution needs improvement in its stability, support and pricing."

"I choose 8 out of 10 for Teradata because there is always the scope for improvement."

More Teradata cons

Pricing and Cost Advice

"There are no licensing costs involved, hence money is saved on the software infrastructure."

"The price of Apache Hadoop could be less expensive."

"We just use the free version."

"If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during storage, for example, though I don't know exactly how much Apache Hadoop costs."

"We don't directly pay for it. Our clients pay for it, and they usually don't complain about the price. So, it is probably acceptable."

"It's reasonable, but there's room for improvement in cost-effectiveness."

"Do take into consider that data storage and compute capacity scale differently and hence purchasing a "boxed" / 'all-in-one" solution (software and hardware) might not be the best idea."

"For any big enterprise the costs can be handled, and it is suitable for big enterprises because the scale of data is large. For medium and small enterprises, the tool is on the high-price side."

More Apache Hadoop pricing and cost advice

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

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

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

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

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

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

"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."

"It comes at a notably high cost for what it offers."

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…

What do you like most about Apache Hadoop?

Top Industries

By visitors reading reviews

Financial Services Firm

29%

Computer Software Company

Government

University

Financial Services Firm

19%

Manufacturing Company

13%

Government

13%

Comms Service Provider

Financial Services Firm

19%

Manufacturing Company

Computer Software Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	14
Midsize Enterprise	8
Large Enterprise	21

By reviewers
Company Size	Count
Small Business	1
Midsize Enterprise	1
Large Enterprise	6

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

Questions from the Community

It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can ...

What is your experience regarding pricing and costs for Apache Hadoop?

The product is open-source, but some associated licensing fees depend on the subscription level. While it might be fr...

What needs improvement with Apache Hadoop?

The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later ...

What needs improvement with Oracle Big Data Appliance?

Areas of Oracle Big Data Appliance that can be improved include the pricing perspective because nowadays they have co...

What is your primary use case for Oracle Big Data Appliance?

The typical use case for Oracle Big Data Appliance, which my clients use, is usually that the customer who has an Ora...

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 d...

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 ...

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 ...

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Compared 5% of the time

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Compared 4% of the time

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Compared 3% of the time

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Product Reports

Apache Hadoop

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Data Warehouse

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Also Known As

No data available

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

Overview

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Apache

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 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.