Databricks vs Oracle Autonomous Data Warehouse comparison

Databricks and Oracle are both solutions in the Cloud Data Warehouse category. Databricks is ranked #7 with an average rating of 8.3, while Oracle is ranked #10 with an average rating of 8.1. Databricks holds a 8.4% mindshare in CDW, compared to Oracle’s 4.6% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 94% of Oracle users who would recommend it.

Databricks

Read 88 Databricks reviews

2,196 Views
1,662 Comparison Views

96% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,145 Views
1,408 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: April 2025).

Buyer's Guide

Databricks vs. Oracle Autonomous Data Warehouse

April 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

7th

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 April 2025, in the Cloud Data Warehouse category, the mindshare of Databricks is 8.4%, up from 3.2% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.6%, up from 3.9% 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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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

"Databricks serves as a single platform that can handle numerous end-to-end machine learning tasks."

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

"Automation with Databricks is very easy when using the API."

"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."

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

"Databricks integrates well with other solutions."

"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."

"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."

More Databricks pros

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

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

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

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

"The solution integrates well with Power BI."

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

"It is a stable and scalable solution."

"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

"There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files."

"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."

"The product should provide more advanced features in future releases."

"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."

"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."

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

"Would be helpful to have additional licensing options."

"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."

More Databricks cons

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

"The installation process is complex. Oracle can make the installation process better."

"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."

"The solution lacks visibility options."

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

"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."

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

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

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

"Price-wise, I would rate Databricks a three out of five."

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

"The pricing depends on the usage itself."

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

More Databricks pricing and cost advice

"The solution's cost is reasonable."

"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 cost is perfect with Oracle Universal credit."

"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."

"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."

"ROI is high."

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

"The solution is expensive."

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

Educational Organization

44%

Financial Services Firm

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...

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

Comparisons

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Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

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Compared 21% of the time

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Compared 21% of the time

Oracle Exadata vs Oracle Autonomous Data Warehouse

Compared 21% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Azure Data Factory vs Oracle Autonomous Data Warehouse

Compared 2% of the time

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Product Reports

Buyer's Guide

Databricks

April 2025

Download Databricks product report

Buyer's Guide

Oracle Autonomous Data Warehouse

April 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

April 2025

Free Report: Databricks vs. Oracle Autonomous Data Warehouse

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