Apache Hadoop vs Oracle Autonomous Data Warehouse comparison

Apache and Oracle are both solutions in the Cloud Data Warehouse category. Additionally, 89% of Apache users are willing to recommend the solution, compared to 95% of Oracle users who would recommend it.

Apache Hadoop

Read 41 Apache Hadoop reviews

1,973 Views
1,144 Comparison Views

89% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,057 Views
1,563 Comparison Views

95% willing to recommend

Apache Hadoop

Oracle Autonomous Data Ware...

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Apache Hadoop and Oracle Autonomous Data Warehouse based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Apache Hadoop vs. Oracle Autonomous Data Warehouse Report (Updated: December 2025).

Buyer's Guide

Apache Hadoop vs. Oracle Autonomous Data Warehouse

December 2025

Download the complete report

Helped 881,082 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:

Categories and Ranking

Apache Hadoop

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Warehouse (7th)

Oracle Autonomous Data Ware...

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (11th)

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.

Read full review

reviewer1297710

IT Administrator at a manufacturing company with 1,001-5,000 employees

Analytics and data security needs are met but optimization requires improvement

We are using Oracle Autonomous Data Warehouse for analytics in my company The solution is used for analytics and it works for our data security needs. We continue to use it with satisfaction. Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not…

Read full review

Quotes from Members

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

Pros

"Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done."

"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."

"The most valuable features are powerful tools for ingestion, as data is in multiple systems."

"One valuable feature is that we can download data."

"Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."

"The most valuable feature is the database."

"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."

"It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming."

More Apache Hadoop pros

"It is a stable and scalable solution."

"One advantage is that if you already have an Oracle Database, it easily integrates with that."

"The performance and scalability are awesome."

"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."

"The solution is used for analytics and it works for our data security needs."

"A very good integration feature that restricts access to unauthorized people."

"Self-patching and runs machine-learning across its logs all the time"

"The product has self-repair features."

More Oracle Autonomous Data Warehouse pros

Cons

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

"The stability of the solution needs improvement."

"The solution is very expensive."

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

"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."

"Hadoop's security could be better."

"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."

More Apache Hadoop cons

"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."

"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace."

"A lot of the tools that were previously there have now been taken away."

"We are not satisfied with the technical support. Their understanding is lacking."

"I would like to see an on-premise solution in the future."

"The initial setup was pretty complex. It was not easy."

"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."

"The solution lacks visibility options."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

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

"The product is open-source, but some associated licensing fees depend on the subscription level."

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

"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."

"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."

"This is a low cost and powerful solution."

"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."

"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."

More Apache Hadoop pricing and cost advice

"Oracle Autonomous Data Warehouse's pricing is fair and reasonable compared to the other cloud vendors."

"ROI is high."

"You pay as you go, and you don't pay for services that you don't use."

"On a scale from one to ten, where one is a low price and ten is a high price, I rate the pricing an eight."

"In terms of architecture and pricing structure, I feel it is a little bit costly compared to Azure. It's fine compared to RedShift, but compared to Azure, it's a bit pricey when you calculate for one TB storage plus around five hours of reporting with the frequency of 1TB data. The cost adds up, making Oracle a bit expensive."

"The solution's cost is reasonable."

"The solution is expensive."

"The licensing cost of the product can vary since you can integrate it very easily with other products or other cloud products...You pay as you use it, so it is not yearly or monthly payments to be made toward Oracle."

More Oracle Autonomous Data Warehouse pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.

See recommendations

881,082 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

34%

Computer Software Company

University

Manufacturing Company

10%

Computer Software Company

Media Company

Insurance 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	7
Midsize Enterprise	1
Large Enterprise	11

Questions from the Community

What do you like most about Apache Hadoop?

It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.

See all answers

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 free for students, organizations typically need to pay for their subscriptions. Th...

See all answers

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 owned it didn't have enough technical resources to properly maintain it. This wa...

See all answers

What is your experience regarding pricing and costs for Oracle Autonomous Data Warehouse?

We pay approximately $70,000 per month. The cost includes maintenance and support.

See all answers

What needs improvement with Oracle Autonomous Data Warehouse?

Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not supported, which is not ideal.

See all answers

What is your primary use case for Oracle Autonomous Data Warehouse?

We are using Oracle Autonomous Data Warehouse for analytics in my company.

See all answers

Comparisons

Snowflake vs Apache Hadoop

Compared 13% of the time

Databricks vs Apache Hadoop

Compared 9% of the time

Teradata vs Apache Hadoop

Compared 9% of the time

Oracle Exadata vs Apache Hadoop

Compared 8% of the time

IBM Netezza Performance Server vs Apache Hadoop

Compared 4% of the time

More Apache Hadoop Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 27% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 16% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 15% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 11% of the time

Snowflake Analytics vs Oracle Autonomous Data Warehouse

Compared 3% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

Apache Hadoop

January 2026

Download Apache Hadoop product report

Buyer's Guide

Oracle Autonomous Data Warehouse

January 2026

Download Oracle Autonomous Data Warehouse product report

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 Autonomous Data Warehouse is the world’s first and only autonomous database optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built for the cloud and optimized using Oracle Exadata, Autonomous Data Warehouse benefits from faster performance and, according to an IDC report (PDF), lowers operational costs by an average of 63%.

Autonomous Database provides the foundation for a data lakehouse—a modern, open architecture that enables you to store, analyze, and understand all your data. The data lakehouse combines the power and richness of data warehouses with the breadth, flexibility, and low cost of popular open source data lake technologies. Access your data lakehouse through Autonomous Database using the world's most powerful and open SQL processing engine.

Oracle

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab

Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank

Buyer's Guide

Apache Hadoop vs. Oracle Autonomous Data Warehouse

December 2025

Free Report: Apache Hadoop vs. Oracle Autonomous Data Warehouse

Find out what your peers are saying about Apache Hadoop vs. Oracle Autonomous Data Warehouse and other solutions. Updated: December 2025.

DOWNLOAD NOW

881,082 professionals have used our research since 2012.

See our Apache Hadoop vs. Oracle Autonomous Data Warehouse report.

See our list of best Cloud Data Warehouse vendors.

We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.