Apache Hadoop vs Oracle Autonomous Data Warehouse comparison

Apache Hadoop vs. Oracle Autonomous Data Warehouse

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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

Apache Hadoop

Average Rating

7.8

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Data Warehouse (7th)

Oracle Autonomous Data Ware...

Average Rating

8.4

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (10th)

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.

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Miodrag Milojevic

Senior Data Archirect at Yettel

A tool for data warehousing that offers scalability, stability, and ease of setup

The initial setup of Oracle Autonomous Data Warehouse is easy and basic, especially if one doesn't use the tricks to get Oracle Exadata for use. One doesn't need to know or be involved in technical stuff to do the setup since, at the least, knowledge might be required when working with some external connections, but it is easy because everything can be done within a couple of clicks. The solution is deployed on the cloud. For deployment, you don't need any technical guidance since you can sit, find it on the web, and prepare an Oracle Autonomous Data Warehouse platform by yourself for free for a limited time. The people needed for the deployment and maintenance depend on the implementation one wants. If you do a simple implementation, you don't need anybody for maintenance since everything is on the cloud. You only have to schedule your backup or see if Oracle can schedule a backup, and you don't take care of the backup. For some more sophisticated or technical implementations, you will need staff for some data warehouse except for some parts of the maintenance like backup, patches, or upgrades since these are a few things you take care of in the background, and you only seek help with the maintenance part, if needed.

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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

"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."

"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."

"Hadoop File System is compatible with almost all the query engines."

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

"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 platform's quick data processing capabilities have been instrumental in supporting our AI-driven projects."

"Its flexibility in handling and storing large volumes of data is particularly beneficial, as is its resilience, which ensures data redundancy and fault tolerance."

"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."

More Apache Hadoop pros

"The solution has a self-backup, so you don't need a DBA (database administrator) to do a backup."

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

"I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."

"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."

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

"The product has self-repair features."

"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."

"It is a very stable tool...It is an extremely scalable tool."

More Oracle Autonomous Data Warehouse pros

Cons

"Since it is an open-source product, there won't be much support."

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

"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."

"I think more of the solution needs to be focused around the panel processing and retrieval of data."

"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 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."

"The load optimization capabilities of the product are an area of concern where improvements are required."

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

More Apache Hadoop cons

"They should make the solution more user-friendly."

"Optimization should be better."

"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."

"It doesn't work well when you have unstructured data or you need online analytics. It is not as nice as Hadoop in these aspects."

"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."

"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."

"An improvement for us would be the inclusion of support for an internal IP, so we could use it directly with the VCN in Oracle Cloud."

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

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

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

"This is a low cost and powerful solution."

"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."

"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."

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

"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."

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

"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

"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."

"Cloud solutions are cheaper, but in the long run, they may not be much cheaper. They certainly have a lower initial cost. The licensing is yearly, and it is based on the size of the hardware and the number of users."

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

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

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

"The cost is perfect with Oracle Universal credit."

"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."

"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

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845,040 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

34%

Computer Software Company

11%

University

Energy/Utilities Company

Educational Organization

49%

Financial Services Firm

Computer Software Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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.

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...

What needs improvement with Apache Hadoop?

Hadoop lacks OLAP capabilities. I recommend adding a Delta Lake feature to make the data compatible with ACID properties. Also, video and audio streaming import issues could be improved to ensure p...

What do you like most about Oracle Autonomous Data Warehouse?

With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main...

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.

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.

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Compared 4% of the time

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Compared 17% of the time

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Product Reports

Apache Hadoop

Download Apache Hadoop product report

Oracle Autonomous Data Warehouse

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

Apache Hadoop vs. Oracle Autonomous Data Warehouse