Databricks vs Workday Prism Analytics comparison

The compared Databricks and Workday solutions aren't in the same category. Databricks is ranked #9 in CDW , with an average rating of 8.4, and holds a 8.3% mindshare in the category. Workday is ranked #17 in BIT , with an average rating of 9.0, and holds a 1.6% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Workday users who would recommend it.

Databricks

Read 91 Databricks reviews

22,527 Views
2,027 Comparison Views

96% willing to recommend

Workday Prism Analytics

Read 5 Workday Prism Analytics reviews

1,535 Views
1,259 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: August 2025).

Buyer's Guide

Cloud Data Warehouse

August 2025

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Helped 867,676 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 (9th), 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 (17th)

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 8.3%, up 5.6% compared to last year.
Workday Prism Analytics, on the other hand, focuses on BI (Business Intelligence) Tools, holds 1.6% mindshare, up 1.3% since last year.

Cloud Data Warehouse Market Share Distribution
Product	Market Share (%)
Databricks	8.3%
Snowflake	17.7%
Dremio	9.4%
Other	64.6%

Cloud Data Warehouse

BI (Business Intelligence) Tools Market Share Distribution
Product	Market Share (%)
Workday Prism Analytics	1.6%
Microsoft Power BI	14.5%
Tableau Enterprise	11.0%
Other	72.9%

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

Anirban Chatterjee

Manager at Deloitte

Provides superior integration capabilities and ability to handle complex data transformations

One area for improvement in the solution is the ability to manually update individual rows or columns of data once it has been uploaded. Any correction requires reloading the entire dataset from the source, which can be inefficient. They should include a feature for granular data updates, allowing users to edit specific entries without reloading entire datasets.

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

"The simplicity of development is the most valuable feature."

"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."

"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."

"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."

"The load distribution capabilities are good, and you can perform data processing tasks very quickly."

"It's great technology."

"Databricks is a robust solution for big data processing, offering flexibility and powerful features."

"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."

More Databricks pros

"Feature-wise, I feel that the solution's stability is 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 customer service and support are pretty good."

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

Cons

"One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle."

"The product cannot be integrated with a popular coding IDE."

"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."

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

"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."

"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."

"The Databricks cluster can be improved."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

More Databricks cons

"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."

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

"It is not a very scalable product."

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

Pricing and Cost Advice

"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."

"The price is okay. It's competitive."

"The product pricing is moderate."

"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."

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

"We're charged on what the data throughput is and also what the compute time is."

"The solution requires a subscription."

More Databricks pricing and cost advice

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

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Financial Services Firm

12%

Insurance Company

Healthcare Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

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 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

What is your primary use case for Workday Prism Analytics?

As a consultant, I use Prism Analytics to implement my client systems. I first have design sessions with them, where we discuss their business gaps and then understand how Workday Prism Analytics c...

See all answers

Comparisons

Dataiku vs Databricks

Compared 9% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau Enterprise vs Databricks

Compared 5% of the time

More Databricks Competitors

Microsoft Power BI vs Workday Prism Analytics

Compared 48% of the time

Tableau Enterprise vs Workday Prism Analytics

Compared 18% of the time

Oracle OBIEE vs Workday Prism Analytics

Compared 5% of the time

Oracle Analytics Cloud vs Workday Prism Analytics

Compared 4% of the time

Oracle Essbase vs Workday Prism Analytics

Compared 3% of the time

More Workday Prism Analytics Competitors

Product Reports

Buyer's Guide

Databricks

September 2025

Download Databricks product report

Buyer's Guide

BI (Business Intelligence) Tools

August 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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