Databricks vs Oracle Analytics Cloud comparison

The compared Databricks and Oracle solutions aren't in the same category. Databricks is ranked #7 in CDW , with an average rating of 8.3, and holds a 7.8% mindshare in the category. Oracle is ranked #8 in BIT , with an average rating of 8.1, and holds a 2.3% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 75% of Oracle users who would recommend it.

Databricks

Read 88 Databricks reviews

2,340 Views
1,659 Comparison Views

96% willing to recommend

Oracle Analytics Cloud

Read 26 Oracle Analytics Cloud reviews

3,919 Views
2,256 Comparison Views

75% willing to recommend

Databricks

Oracle Analytics Cloud

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Executive Summary

We performed a comparison between Databricks and Oracle Analytics Cloud 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 Analytics Cloud Report (Updated: February 2023).

Buyer's Guide

Databricks vs. Oracle Analytics Cloud

February 2023

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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

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 Analytics Cloud

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

BI (Business Intelligence) Tools (8th), Data Visualization (6th)

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 7.8%, up 2.9% compared to last year.
Oracle Analytics Cloud, on the other hand, focuses on BI (Business Intelligence) Tools, holds 2.3% mindshare, down 2.8% since last year.

Cloud Data Warehouse

BI (Business Intelligence) Tools

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.

Read full review

Hafiz Abdul Mannan

Senior Consultant Oracle Technologies at Hewlett Packard Enterprise

Empowers your entire organization to ask any question of any data—across any environment, on any device

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.

Read full review

Quotes from Members

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

Pros

"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."

"The ability to stream data and the windowing feature are valuable."

"In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."

"It helps integrate data science and machine learning capabilities."

"The integration with Python and the notebooks really helps."

"The processing capacity is tremendous in the database."

"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."

"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."

More Databricks pros

"It's really an enterprise solution. It has a dashboard, like standard dashboarding functionality. It also has reporting capabilities for producing pixel-perfect reports, bursting large volumes of a document if you need to. It has interactive data discovery functionality, which you would use to explore your data, bring your own data, and merge it with maybe the data from an enterprise data warehouse to get new insights from the pre-existing data. It has machine learning embedded in the solution. If you're new to machine learning, it's a really good way to get into it, because it's all within this platform, and it's really easy to use."

"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."

"It plays a crucial role in facilitating decision-making for various organizational stakeholders."

"Oracle Analytics Cloud's most valuable feature is its visualization."

"The ability to quickly search for and access relevant data is crucial."

"The specific capability I find important in Oracle Analytics Cloud is that it allows the basic user to easily drag and drop data. I also like that the solution allows the user to decide what to measure and what to see in the reports."

"The solution is user-friendly."

"The best feature may be data flow, which is used to prepare and clean data."

More Oracle Analytics Cloud 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."

"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

"I would like it if Databricks made it easier to set up a project."

"I think setting up the whole account for one person and giving access are areas that can be difficult to manage and should be made a little easier."

"The initial setup is difficult."

"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."

"It should have more compatible and more advanced visualization and machine learning libraries."

More Databricks cons

"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."

"It is less scalable than Snowflake."

"Analytics Cloud allows you to merge various data types and structure data from multiple sources."

"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 implementation of generative AI and machine learning should improve"

"The solution could be more flexible."

"Sharing dataflows is not possible at this time, and the custom chart functionality is not available."

"The product could benefit from increased flexibility compared to other vendors."

More Oracle Analytics Cloud cons

Pricing and Cost Advice

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

"The solution requires a subscription."

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

"Databricks are not costly when compared with other solutions' prices."

"The price of Databricks is reasonable compared to other solutions."

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

"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."

"I would rate Databricks' pricing seven out of ten."

More Databricks pricing and cost advice

"I would rate it a five out of five in terms of the value received for the price charge."

"The price is reasonable; it's quite a bit lower than Tableau and Spotfire."

"Oracle Analytics Cloud's pricing is generally higher than that of other vendors."

"We pay on a monthly basis and it is $10 per user each month."

"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"

"Bottom line, the cost is really, really cheap compared to other solutions. Oracle has made a huge effort on the pricing."

"The product’s pricing is expensive. However, feature-wise, it fits the requirements of enterprise customers."

More Oracle Analytics Cloud pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Educational Organization

39%

Financial Services Firm

Computer Software Company

Government

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 ...

See all answers

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

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...

See all answers

What do you like most about Oracle Analytics Cloud?

The ability to quickly search for and access relevant data is crucial.

See all answers

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...

See all answers

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 8% of the time

Amazon SageMaker vs Databricks

Compared 6% of the time

More Databricks Competitors

Oracle OBIEE vs Oracle Analytics Cloud

Compared 24% of the time

Microsoft Power BI vs Oracle Analytics Cloud

Compared 14% of the time

Oracle Business Intelligence Cloud Service vs Oracle Analytics Cloud

Compared 11% of the time

Tableau vs Oracle Analytics Cloud

Compared 9% of the time

SAP Analytics Cloud vs Oracle Analytics Cloud

Compared 7% of the time

More Oracle Analytics Cloud Competitors

Product Reports

Buyer's Guide

Databricks

March 2025

Download Databricks product report

Buyer's Guide

Oracle Analytics Cloud

March 2025

Download Oracle Analytics Cloud product report

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

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 Analytics is a complete platform with ready-to-use services for a wide variety of workloads and data.

Oracle Analytics allows businesses to add AI and machine learning capabilities to any application—and as part of our integrated suite of cloud services to comply with data security and connected without disrupting business operations.

Offering valuable, actionable insights from all types of data—in the cloud, on-premises, or in a hybrid deployment—Oracle Analytics empowers business users, data engineers, and data scientists to access and process relevant data, evaluate predictions, and make quick, accurate decisions.

Oracle Analytics Cloud Features

Oracle Analytics Cloud has many valuable key features. Some of the most useful ones include:

Intelligent search
Smart data discovery
Smart data preparation
Natural language
Auto suggest
Visualization
Dashboarding
Global transformation policies
Smart collaboration
Integrated data science
Enterprise architecture and security
Platform extensibility
Smart data connectors

Oracle Analytics Cloud Benefits

There are many benefits to implementing Oracle Analytics Cloud. Some of the biggest advantages the solution offers include:

Flexibility: Oracle Analytics Cloud gives you the flexibility to grow and change as your business does. At the same time, it puts you in complete control of your analytics environment by allowing you to analyze data and accommodate changing demand easily.

Scalable: Oracle Analytics Cloud is a single, centralized solution that provides everything you need in a scalable environment to support varied user requirements for your organization right now and in the future as well.

Comprehensive analytics: With Oracle Analytics Cloud, existing services are combined with new ones to deliver comprehensive analytics in the cloud. It provides everything you need for analytic agility, from fast, fluid self-service discovery to data loading and blending, inline data prep, data enrichment, automatic visualizations, data storytelling, and more.

Cost-effectiveness: The solution is cost-effective and reduces your total cost of ownership (TCO).
Innovation: Use the latest data analytics technologies, such as AI, machine learning, and natural language processing. Oracle Analytics has been recognized by industry experts for its innovations and robust architecture.

Reviews from Real Users

Below are some reviews and helpful feedback written by PeerSpot users currently using the Oracle Analytics Cloud solution.

Fabricio Q., Data Analytics Manager, says, “The main functionality is great and everything is pretty standard and easy to use. It's great for consolidation and creating one source of truth. The initial setup is pretty straightforward.”

PeerSpot user, Eric B., Independent Consultant - Oracle BI Applications at Desjardins, mentions “It's really an enterprise solution. It has standard dashboarding functionality. It also has reporting capabilities for producing pixel-perfect reports, bursting large volumes of a document if you need to. It has interactive data discovery functionality, which you would use to explore your data, bring your own data, and merge it with maybe the data from an enterprise data warehouse to get new insights from the pre-existing data. It has machine learning embedded in the solution.”

Gaurav S., Vice President Credit Risk Management at a financial services firm, explains, “From a financial or bank perspective, this product is secure enough. The dashboards, analytics, visualizations, and different reports are valuable for business analytics. The AI/ML enablement is useful, as many reporting tools do not offer machine learning models as of now, without writing customized code.”

Another reviewer, Trinh P., Delivery Manager at Sift Ag, comments, "The specific capability I find important in Oracle Analytics Cloud is that it allows the basic user to easily drag and drop data. I also like that the solution allows the user to decide what to measure and what to see in the reports."

Oracle

Sample Customers

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

Sejong Hospital

Buyer's Guide

Databricks vs. Oracle Analytics Cloud

February 2023

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