Apache Hadoop vs Oracle Big Data Appliance vs Teradata comparison

Oracle Big Data Appliance

Read 77 Teradata reviews

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87% willing to recommend

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: August 2025).

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Data Warehouse

August 2025

Helped 868,654 peers since 2012

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 October 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 4.3%, down from 5.1% compared to the previous year. The mindshare of Oracle Big Data Appliance is 1.6%, up from 1.1% compared to the previous year. The mindshare of Teradata is 12.1%, down from 16.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse Market Share Distribution
Product	Market Share (%)
Teradata	12.1%
Apache Hadoop	4.3%
Oracle Big Data Appliance	1.6%
Other	82.0%

Data Warehouse

Featured Reviews

Sushil Arya

Software developer at Fiserv

Provides ease of integration with the IT workflow of a business

When working with Kafka, I saw that the data came in an incremental order. The incremental data processing part is still not very effective in Apache Hadoop. If the data is already there, it can be processed very effectively, especially if the data is coming in every second. If you want to know the location of some data every second, then such data is not processed effectively in Apache Hadoop. I can say that one of the features where improvements are required revolves around the licensing cost of the tool. If the tool can build some licensing structures in a pay-per-use manner, organizations can get the look and feel of Apache Hadoop. Apache Hadoop can offer a licensing structure of the product that can be seen as similar to how AWS operates. Apache Hadoop can look into the capability of processing incremental data. The tool's setup process can be a scope of improvement. Also, it is not very simple because while doing the setup, we need to do all the server settings, including port listing and firewall configurations. If we look at other products on the market, then they can be made simpler. There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required. The time frame for the resolution is an area that needs to be improved. The overall communication part of the technical support team also needs improvement.

Provides clean, centralized data

Mohammed Hamad

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

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.

Has improved data quality, optimized reporting processes, and enabled predictive insights across business units

Kirk Robinson

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

The limitation we encountered was related to speed, prompting us to increase our AWS cloud thresholds and benchmarks on the servers, adding more throughput. We have been testing that, but speed remains one of our key issues. The integration has been awesome because of the platforms and their usage, and usability is great. The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts. If Teradata could provide a list of certified experts, that would be fantastic. I rated Teradata a nine because the main area for improvement is the bandwidth of resources that could assist us in applying to our projects, specifically more certified and expert resources. The market share of Teradata professionals is limited, creating an issue for us.

More Apache Hadoop pricing and cost advice

Quotes from Members

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

Pros

"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."

"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."

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

"It's good for storing historical data and handling analytics on a huge amount of data."

"The performance is pretty good."

"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."

"The best thing about this solution is that it is very powerful and very cheap."

"I recommend it for the telecom sector. I know it well, and it's a good fit."

More Apache Hadoop pros

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

"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."

"It's very, very fast"

"The tool's most valuable feature is the warehousing model."

"It's the same as your visual database. I like the fast load feature for data, the BTQ solution is very good, and storage procedures are very fast."

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

"Designing the database is easy."

"It is a highly robust software solution."

"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."

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

More Teradata pros

Cons

"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."

"It could be more user-friendly."

"Hadoop lacks OLAP capabilities."

"The product's availability of comprehensive training materials could be improved for faster onboarding and skill development among team members."

"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."

"It needs better user interface (UI) functionalities."

"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."

"I would like to see more direct integration of visualization applications."

More Apache Hadoop cons

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

"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."

"Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve."

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

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

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

"The scalability could be better. The on-premises solution is always more complicated to scale."

"The initial setup was complex as we had to rewrite a lot of the code."

"Teradata needs to expand the kind of training that's available to customers. Teradata only offers training directly and doesn't delegate to any third-party companies. As a result, it's harder to find people trained on Teradata in our market relative to Oracle."

More Teradata cons

Pricing and Cost Advice

"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."

"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."

"We just use the free version."

"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."

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

"This is a low cost and powerful solution."

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

"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."

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

"Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions."

"Teradata is a very expensive solution."

"The solution requires a license."

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

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

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

"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."

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

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

35%

Computer Software Company

10%

University

Government

No data available

Financial Services Firm

25%

Computer Software Company

Manufacturing Company

Healthcare 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	26
Midsize Enterprise	12
Large Enterprise	49

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 ...

Oracle Exadata vs Apache Hadoop

Comparisons

Compared 21% of the time

Databricks vs Apache Hadoop

Compared 13% of the time

Azure Data Factory vs Apache Hadoop

Compared 12% of the time

Snowflake vs Apache Hadoop

Compared 10% of the time

BigQuery vs Apache Hadoop

Compared 10% of the time

More Apache Hadoop Competitors

Oracle Exadata vs Oracle Big Data Appliance

Compared 100% of the time

More Oracle Big Data Appliance Competitors

Oracle Exadata vs Teradata

Compared 11% of the time

IBM Db2 Database vs Teradata

Compared 8% of the time

Snowflake vs Teradata

Compared 7% of the time

SQL Server vs Teradata

Compared 7% of the time

Palantir Foundry vs Teradata

Compared 2% of the time

More Teradata Competitors

Product Reports

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Apache Hadoop

September 2025

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Data Warehouse

August 2025

Download Teradata product report

September 2025

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.