Databricks vs Oracle Big Data Appliance comparison

Databricks and Oracle are both solutions in the Cloud Data Warehouse category. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 71% of Oracle users who would recommend it.

Databricks

Read 89 Databricks reviews

2,196 Views
1,662 Comparison Views

96% willing to recommend

Oracle Big Data Appliance

Read 5 Oracle Big Data Appliance reviews

381 Views
251 Comparison Views

71% willing to recommend

Databricks

Oracle Big Data Appliance

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Databricks and Oracle Big Data Appliance 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 Big Data Appliance Report (Updated: April 2025).

Buyer's Guide

Databricks vs. Oracle Big Data Appliance

April 2025

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Helped 850,028 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

Databricks

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th), Data Science Platforms (1st), Streaming Analytics (1st)

Oracle Big Data Appliance

Average Rating

8.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

Data Warehouse (19th)

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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Mohammed Hamad

AI & Data Engineering Lead at a tech services company with 10,001+ employees

Provides clean, centralized data

From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera. Oracle could also improve Big Data Appliance by having one technology on their stack and working on it instead of continually changing the name or technologies or features. In addition, they could have a program to enable their partners to use this technology because right now, I have to have an expert to use the AI elements.

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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

"The tool helps with data processing and analytics with large-scale data or big data since it is associated with managing data at a large scale."

"I like cloud scalability and data access for any type of user."

"We can scale the product."

"The solution is very easy to use."

"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."

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

"It is a cost-effective solution."

"It's easy to increase performance as required."

More Databricks pros

"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."

"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."

"This is a comprehensive solution that is easy to deploy."

Cons

"Databricks can improve by making the documentation better."

"Costs can quickly add up if you don't plan for it."

"It would be very helpful if Databricks could integrate with platforms in addition to Azure."

"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."

"There are no direct connectors — they are very limited."

"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."

"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."

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

More Databricks cons

"The product should be simplified for the average user."

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

Pricing and Cost Advice

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

"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

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

"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."

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

More Databricks pricing and cost advice

"Oracle's prices are too high compared to others in the market."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Financial Services Firm

32%

Computer Software Company

15%

Government

11%

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...

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Comparisons

Dataiku vs Databricks

Compared 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Dremio vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

Oracle Exadata vs Oracle Big Data Appliance

Compared 75% of the time

Apache Hadoop vs Oracle Big Data Appliance

Compared 25% of the time

More Oracle Big Data Appliance Competitors

Product Reports

Buyer's Guide

Databricks

April 2025

Download Databricks product report

Buyer's Guide

Data Warehouse

April 2025

Download Oracle Big Data Appliance 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 Big Data Appliance is a flexible, high-performance, secure platform for running diverse workloads on Hadoop and NoSQL systems. With Oracle Big Data SQL, Oracle Big Data Appliance extends Oracle’s industry-leading implementation of SQL to Hadoop and NoSQL systems. By combining the newest technologies from the Hadoop ecosystem and powerful Oracle SQL capabilities together on a single pre-configured platform, Oracle Big Data Appliance is uniquely able to support rapid development of new Big Data applications and tight integration with existing relational data.

For more information on Oracle Big Data Appliance, visit Oracle.com

Oracle

Sample Customers

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

Caixa Bank

Buyer's Guide

Databricks vs. Oracle Big Data Appliance

April 2025

Free Report: Databricks vs. Oracle Big Data Appliance

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