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 #10 with an average rating of 8.1. Databricks holds a 8.9% mindshare in CDW, compared to Oracle’s 4.8% 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

2,200 Views
88 Comparison Views

96% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

1,853 Views
1,131 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: June 2025).

Buyer's Guide

Databricks vs. Oracle Autonomous Data Warehouse

June 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

10th

Average Rating

8.4

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Cloud Data Warehouse category, the mindshare of Databricks is 8.9%, up from 4.1% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.8%, up from 4.1% 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

"It's very simple to use Databricks Apache Spark."

"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."

"The initial setup phase of Databricks was good."

"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."

"Databricks is a scalable solution. It is the largest advantage of the solution."

"It is fast, it's scalable, and it does the job it needs to do."

"We have the ability to scale, collaborate and do machine learning."

"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."

More Databricks pros

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

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

"It is a stable and scalable solution."

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

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

"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."

"The solution integrates well with Power BI."

"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 reason we use it."

More Oracle Autonomous Data Warehouse pros

Cons

"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."

"In the next release, I would like to see more optimization features."

"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."

"Anyone who doesn't know SQL may find the product difficult to work with."

"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."

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

"I would like it if Databricks adopted an interface more like R Studio. When I create a data frame or a table, R Studio provides a preview of the data. In R Studio, I can see that it created a table with so many columns or rows. Then I can click on it and open a preview of that data."

"The API deployment and model deployment are not easy on the Databricks side."

More Databricks cons

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

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

"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."

"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."

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

"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."

"There is a need for more storage to be allocated, but over a period of time, it becomes impossible to reduce it after using it."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."

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

"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 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 licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."

"The price is okay. It's competitive."

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

More Databricks pricing and cost advice

"The price depends on the configuration we choose."

"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."

"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."

"The solution's cost is reasonable."

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

"ROI is high."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Educational Organization

31%

Financial Services Firm

10%

Computer Software Company

Manufacturing Company

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...

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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

June 2025

Download Databricks product report

Buyer's Guide

Oracle Autonomous Data Warehouse

May 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

June 2025

Free Report: Databricks vs. Oracle Autonomous Data Warehouse

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