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Databricks vs Oracle Big Data Appliance comparison

 

Comparison Buyer's Guide

Executive Summary

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
88
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
5
Ranking in other categories
Data Warehouse (19th)
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
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.
Mohammed Hamad - PeerSpot reviewer
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"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."
"It's very simple to use Databricks Apache Spark."
"Easy to use and requires minimal coding and customizations."
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"The time travel feature is the solution's most valuable aspect."
"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"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."
"This is a comprehensive solution that is easy to deploy."
"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."
 

Cons

"Anyone who doesn't know SQL may find the product difficult to work with."
"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."
"I have seen better user interfaces, so that is something that can be improved."
"Databricks can improve by making the documentation better."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"Would be helpful to have additional licensing options."
"Doesn't provide a lot of credits or trial options."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."
"The product should be simplified for the average user."
"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

"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."
"I would rate Databricks' pricing seven out of ten."
"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."
"The cost is around $600,000 for 50 users."
"I rate the price of Databricks as eight out of ten."
"We're charged on what the data throughput is and also what the compute time is."
"I would rate the tool’s pricing an eight out of ten."
"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."
"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
17%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
31%
Computer Software Company
15%
Government
10%
University
7%
 

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 ...
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...
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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Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
No data available
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Caixa Bank
Find out what your peers are saying about Databricks vs. Oracle Big Data Appliance and other solutions. Updated: March 2025.
848,207 professionals have used our research since 2012.