Try our new research platform with insights from 80,000+ expert users

Databricks vs Oracle Analytics Cloud 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
92
Ranking in other categories
Cloud Data Warehouse (9th), Data Science Platforms (1st), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)
Oracle Analytics Cloud
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
27
Ranking in other categories
BI (Business Intelligence) Tools (14th), Data Visualization (10th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 9.2%, up 6.7% compared to last year.
Oracle Analytics Cloud, on the other hand, focuses on BI (Business Intelligence) Tools, holds 1.3% mindshare, down 2.4% since last year.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Databricks9.2%
Snowflake16.1%
Teradata8.5%
Other66.2%
Cloud Data Warehouse
BI (Business Intelligence) Tools Market Share Distribution
ProductMarket Share (%)
Oracle Analytics Cloud1.3%
Microsoft Power BI9.4%
Tableau Enterprise6.7%
Other82.6%
BI (Business Intelligence) Tools
 

Featured Reviews

SimonRobinson - PeerSpot reviewer
Governance And Engagement Lead
Improved data governance has enabled sensitive data tracking but cost management still needs work
I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.
Vaclav-Biba - PeerSpot reviewer
BI/DW Consultant at Neit Consulting
Enhanced analytics through metadata-driven reporting with enterprise-level visualizations enables competitive advantage
In my opinion, what can be better in Oracle Analytics Cloud these days is primarily about pricing. I am from the Czech Republic, which is our main market. The situation here in the Czech Republic is that Power BI rules the world. There are two main reasons for this. First, speaking about the Czech Republic specifically, and second, the Power BI pricing model appears cheaper compared to Oracle Analytics Cloud. The pricing model in Microsoft is more straightforward. With Oracle, you have the data visualization and enterprise lines, and to put it simply, both appear as more expensive options for customers trying to get oriented in the segment.

Quotes from Members

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

Pros

"The setup is quite easy."
"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."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"The solution is very easy to use."
"It offers AI functionalities that assist with code management and machine learning processes."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"The simplicity of development is the most valuable feature."
"The initial setup is pretty easy."
"It's robust. It has the ability to handle massive amounts. After reporting has been developed, there is an ease of use or a user-friendly interface for a trained workforce."
"I've discovered that the new layout of this product makes Docker sharing, machine learning support, and data backups more efficient. Unlike the older method of linking physical, pre-logical, and presentation layers separately, the new interface simplifies this process. Additionally, the integration of databases and machine learning is seamless, with the new visualization approach being particularly beautiful and highly beneficial."
"The most valuable features of the solution are dashboarding and data visualization."
"The product is able to compare with other tools on the market; it has everything you need, everything you can find in other tools such as Tableau and Power BI, and additionally, it has history, so you get a robust solution with support."
"Analytics Cloud allows you to merge various data types and structure data from multiple sources."
"It's valuable feature is that it is user-friendly and doesn't require much time for understanding. The solution is stable. The initial setup was straightforward."
"A valuable feature is the speed of the solution."
"Data preparation is fantastic and fast. We were able to use multiple data sources and prepare the data quickly."
 

Cons

"The pricing of Databricks could be cheaper."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"I believe that this product could be improved by becoming more user-friendly."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"It's not a failure of the product; it's just an architectural choice. It has to do with data modeling. I'm comparing this to another product, which is Oracle's developer client and probably called Oracle BI Developer Client Tool. The data modeler, which is cloud-based, and Oracle BI Developer Client Tool, which is local or on-premises-based, both can do the same thing in data modeling. However, the cloud tool does not have as many features as the Oracle BI Developer Client Tool, which is closest to the OBIEE Administration Tool with full feature data modeling, metadata development, and so forth. In a complex environment or implementation, that is the capability that you need."
"The implementation of generative AI and machine learning should improve"
"The migration of older dash tools from the classic interface of Oracle BI prior to OAS launch to the newer Data Visualization and Oracle Analytics Cloud interfaces, including dashboards and metadata, is currently a cumbersome process. Improvements in this area would be highly beneficial. Additionally, the administration of the cloud, particularly the startup of services and linking of the WebLogic server and integrated components, takes longer than desired. In today's enterprise landscape, waiting forty minutes for the server to be operational is quite lengthy; ideally, this process should take a maximum of four minutes. It would be excellent to incorporate metadata management as an integral part of the Oracle Analytics Cloud. When dealing with integrated data from various sources, tracking data lineage and the entire data life cycle, from sources to report development and the mapping of reports to specific dashboards, should be seamlessly managed within the Oracle Analytics Cloud. This would eliminate the need for additional tools. Drawing a comparison, tools like Tableau have a feature enabling metadata management, making it easier to trace the complete data lineage of reports. Managing over seven hundred and thirty-six business dashboards, the metadata management capability within Tableau simplified the process of understanding how reports were developed, including details like associated tables, users, linked views, materialized views, data segmentations, ETL jobs, and the data warehouse stages. Enhancing metadata tracking within the Oracle Analytics Cloud layout would facilitate easy and practical management of the complete data life cycle, encompassing user accessibility and report permissions."
"The product should improve its user interface. It should be welcoming and modern. Developers should also find it easier to build data models. Oracle Analytics Cloud needs to have better visualizations and more options in the marketplace."
"The product should be improved in terms of connectors; right now the top twenty connectors are available, but OneDrive and Teradata are missing."
"The pricing model in Microsoft is more straightforward. With Oracle, you have the data visualization and enterprise lines, and to put it simply, both appear as more expensive options for customers trying to get oriented in the segment."
"At this time, dataflows cannot be shared, but I think that this should be enhanced."
"Oracle Analytics Cloud is lacking in charts. They should add more charts to it."
 

Pricing and Cost Advice

"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 would rate Databricks' pricing seven out of ten."
"I would rate the tool’s pricing an eight out of ten."
"We're charged on what the data throughput is and also what the compute time is."
"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."
"The product pricing is moderate."
"The billing of Databricks can be difficult and should improve."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"The product’s pricing is expensive. However, feature-wise, it fits the requirements of enterprise customers."
"The tool's pricing is not unreasonable or non-competitive."
"I rate the product's pricing a nine on a scale of one to ten, where one is cheap, and ten is expensive."
"A highly cost-effective solution"
"We pay on a monthly basis and it is $10 per user each month."
"I would rate it a five out of five in terms of the value received for the price charge."
"Oracle Analytics Cloud's pricing is generally higher than that of other vendors."
"The price is reasonable; it's quite a bit lower than Tableau and Spotfire."
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
881,082 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
9%
Healthcare Company
6%
Government
14%
Financial Services Firm
9%
Manufacturing Company
9%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business25
Midsize Enterprise12
Large Enterprise56
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise7
Large Enterprise11
 

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...
Which Oracle product is better - OBIEE or Analytics Cloud?
Oracle OBIEE is designed to be relatively easy to set up and has a helpful customer support staff at the ready to assist customers. These are two attributes that make this system quite valuable. OB...
What do you like most about Oracle Analytics Cloud?
The ability to quickly search for and access relevant data is crucial.
What is your experience regarding pricing and costs for Oracle Analytics Cloud?
The pricing of Oracle Analytics Cloud is quite expensive, fitting for a premium tool. However, the cost raises expectations for partner support that are not met, especially for smaller companies wh...
 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Oracle Analytics Cloud Service, OAC, Oracle Data Visualization, Oracle Data Visualization Cloud Service, ODV
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Sejong Hospital
Find out what your peers are saying about Databricks vs. Oracle Analytics Cloud and other solutions. Updated: February 2023.
881,082 professionals have used our research since 2012.