Databricks vs Workday Prism Analytics comparison

The compared Databricks and Workday 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. Workday is ranked #13 in BIT , with an average rating of 8.6, and holds a 1.7% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Workday users who would recommend it.

Databricks

Read 88 Databricks reviews

2,340 Views
1,659 Comparison Views

96% willing to recommend

Workday Prism Analytics

Read 5 Workday Prism Analytics reviews

1,247 Views
1,118 Comparison Views

100% willing to recommend

Databricks

Workday Prism Analytics

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Databricks and Workday Prism Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: March 2025).

Buyer's Guide

Cloud Data Warehouse

March 2025

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Helped 842,296 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)

Workday Prism Analytics

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

BI (Business Intelligence) Tools (13th)

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.
Workday Prism Analytics, on the other hand, focuses on BI (Business Intelligence) Tools, holds 1.7% mindshare, up 1.1% 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

Sarvesh Kumar Jha

Senior Technology Consultant at PricewaterhouseCoopers

Provides great flexibility in terms of data transformation

I really like the flexibility the solution provides in terms of data transformation. Workday introduced Prism Analytics mainly because many clients wanted to merge data from different systems and then work with it to get some insights out of it. For that, they previously used tools like Power BI. Workday Prism Analytics gives you the power to do all the data transformations within Workday itself without taking out crucial data to a third system. I really like the way Workday has enabled Prism Analytics to be that one solution where you can bring everything. It also provides you the flexibility that things like the security model of Workday are still in place. You don't have to redo your security configuration if you do the data transformation outside Workday.

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

"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."

"Databricks serves as a single platform for conducting the entire end-to-end lifecycle of machine learning models or AI ops."

"I would rate them ten out of ten."

"We have the ability to scale, collaborate and do machine learning."

"The initial setup phase of Databricks was good."

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

"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."

"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."

More Databricks pros

"The customer service and support are pretty good."

"The product is easier to use compared to other applications."

"I really like the flexibility the solution provides in terms of data transformation."

"The solution is stable and reliable, with minimal issues affecting its performance."

"Feature-wise, I feel that the solution's stability is good."

Cons

"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."

"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."

"There would also be benefits if more options were available for workers, or the clusters of the two points."

"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."

"The Databricks cluster can be improved."

"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."

"It would be great if Databricks could integrate all the cloud platforms."

"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."

More Databricks cons

"When you create certain objects, a lot of the time, the fields are text. They’re not numeric, date, or any other field type"

"There is not much flexibility in how we can add external data within Workday Prisma Analytics."

"One area for improvement in the solution is the ability to manually update individual rows or columns of data once it has been uploaded."

"The visualization techniques must be upgraded."

"It is not a very scalable product."

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."

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

"The cost is around $600,000 for 50 users."

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

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."

"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."

"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 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."

More Databricks pricing and cost advice

"The solution is very expensive."

"I do not know of the licensing cost, but there are additional costs like 5,00,000 for recruitment modules."

"Based on whatever I have heard, Workday Prism Analytics is considered an expensive tool."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

10%

Computer Software Company

Insurance Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

What do you like most about Workday Prism Analytics?

Feature-wise, I feel that the solution's stability is good.

See all answers

What is your experience regarding pricing and costs for Workday Prism Analytics?

Based on whatever I have heard, Workday Prism Analytics is considered an expensive tool. In fact, that has been one of the hindrance factors for Workday in making Prism Analytics more sellable.

See all answers

What needs improvement with Workday Prism Analytics?

I think there are still some gaps in the solution. There is not much flexibility in how we can add external data within Workday Prisma Analytics. For now, Workday has enabled the SFTP server and Am...

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

Microsoft Power BI vs Workday Prism Analytics

Compared 48% of the time

Tableau vs Workday Prism Analytics

Compared 20% of the time

Oracle OBIEE vs Workday Prism Analytics

Compared 4% of the time

Alteryx vs Workday Prism Analytics

Compared 3% of the time

Amazon QuickSight vs Workday Prism Analytics

Compared 3% of the time

More Workday Prism Analytics Competitors

Product Reports

Buyer's Guide

Databricks

March 2025

Download Databricks product report

Buyer's Guide

BI (Business Intelligence) Tools

February 2025

Download Workday Prism Analytics product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Prism Analytics

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

With Workday Prism Analytics, you can bring data in at scale from any source and prepare, analyze, and securely share it with your organization. The result? You gain all the insights you need to drive better business outcomes.

Workday

Sample Customers

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

Denny's

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