Databricks vs Oracle Autonomous Data Warehouse comparison

Databricks and Oracle are both solutions in the Cloud Data Warehouse category. Databricks is ranked #8 with an average rating of 8.3, while Oracle is ranked #11 with an average rating of 7.8. Databricks holds a 8.5% mindshare in CDW, compared to Oracle’s 5.0% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 94% of Oracle users who would recommend it.

Databricks

Read 91 Databricks reviews

23,965 Views
2,157 Comparison Views

96% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,265 Views
1,631 Comparison Views

94% willing to recommend

Databricks

Oracle Autonomous Data Ware...

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Executive Summary

We performed a comparison between Databricks 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 Databricks vs. Oracle Autonomous Data Warehouse Report (Updated: July 2025).

Buyer's Guide

Databricks vs. Oracle Autonomous Data Warehouse

July 2025

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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

Databricks

Ranking in Cloud Data Warehouse

8th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Science Platforms (1st), Streaming Analytics (1st)

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

11th

Average Rating

8.4

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Cloud Data Warehouse category, the mindshare of Databricks is 8.5%, up from 5.1% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.0%, up from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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Kwajah Mohiuddin

Global Head of Architecture at a financial services firm with 1,001-5,000 employees

Provides self-repair features, but the setup is complex

We use the product for online applications. We use it in the financial industry The product has self-repair features. The tool tunes itself. It separates compute from storage. We can scale storage and compute separately. The setup is complex. Oracle is a complex tool. I have been using Oracle…

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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

"Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."

"Databricks helps crunch petabytes of data in a very short period of time."

"I work in the data science field and I found Databricks to be very useful."

"Databricks' capability to process data in parallel enhances data processing speed."

"Databricks is a robust solution for big data processing, offering flexibility and powerful features."

"The initial setup phase of Databricks was good."

"We can scale the product."

"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."

More Databricks pros

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

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

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

"The analytics have been very good. We've found them to be quite useful."

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

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

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

"The product has self-repair features."

More Oracle Autonomous Data Warehouse pros

Cons

"A lot of people are required to manage this solution."

"Cluster failure is one of the biggest weaknesses I notice in our Databricks."

"I believe that this product could be improved by becoming more user-friendly."

"There is room for improvement in visualization."

"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."

"Databricks could improve in some of its functionality."

"It's not easy to use, and they need a better UI."

"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."

More Databricks cons

"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."

"The setup is complex."

"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."

"Ease of connectivity could be improved."

"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."

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

"Optimization should be better."

"Oracle Autonomous Data Warehouse is not available as an on-premises solution."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

"We only pay for the Azure compute behind the solution."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."

"The solution is a good value for batch processing and huge workloads."

"I rate the price of Databricks as eight out of ten."

"It is an expensive tool. The licensing model is a pay-as-you-go one."

"The billing of Databricks can be difficult and should improve."

More Databricks 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."

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

"The price depends on the configuration we choose."

"The solution is expensive."

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

"The cost is perfect with Oracle Universal credit."

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

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Computer Software Company

11%

Financial Services Firm

Manufacturing Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

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How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

See all answers

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

See all answers

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...

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

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Product Reports

Buyer's Guide

Databricks

August 2025

Download Databricks product report

Buyer's Guide

Oracle Autonomous Data Warehouse

August 2025

Download Oracle Autonomous Data Warehouse product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Databricks

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

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

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

Buyer's Guide

Databricks vs. Oracle Autonomous Data Warehouse

July 2025

Free Report: Databricks vs. Oracle Autonomous Data Warehouse

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