Databricks vs Workday Prism Analytics comparison

The compared Databricks and Workday solutions aren't in the same category. Databricks is ranked #8 in CDW , with an average rating of 8.3, and holds a 9.0% mindshare in the category. Workday is ranked #17 in BIT , with an average rating of 9.0, and holds a 1.9% 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

2,043 Views
109 Comparison Views

96% willing to recommend

Workday Prism Analytics

Read 5 Workday Prism Analytics reviews

1,202 Views
971 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: June 2025).

Buyer's Guide

Cloud Data Warehouse

June 2025

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Helped 860,592 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 (8th), 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 9.0%, up 4.6% compared to last year.
Workday Prism Analytics, on the other hand, focuses on BI (Business Intelligence) Tools, holds 1.9% mindshare, up 1.2% 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

"I think Databricks is very good at facilitating AI and machine learning projects; they implement AI and machine learning models very well, and clients can run their models on Databricks."

"The solution is built from Spark and has integration with MLflow, which is important for our use case."

"Automation with Databricks is very easy when using the API."

"Databricks' capability to process data in parallel enhances data processing speed."

"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."

"Databricks has a Unified Catalog that assists with secured access and governance."

"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."

"I haven't heard about any major stability issues. At this time I feel like it's stable."

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

"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."

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

"Costs can quickly add up if you don't plan for it."

"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."

"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."

"Cluster failure is one of the biggest weaknesses I notice in our Databricks."

"The initial setup of Databricks could be complex."

"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."

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"

"The visualization techniques must be upgraded."

"It is not a very scalable product."

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

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

Pricing and Cost Advice

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"Databricks uses a price-per-use model, where you can use as much compute as you need."

"The billing of Databricks can be difficult and should improve."

"The solution requires a subscription."

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

"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."

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

More Databricks pricing and cost advice

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

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

"The solution is very expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Financial Services Firm

11%

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 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 10% 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 7% of the time

Tableau vs Databricks

Compared 5% of the time

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Microsoft Power BI vs Workday Prism Analytics

Compared 48% of the time

Tableau vs Workday Prism Analytics

Compared 18% of the time

Oracle OBIEE vs Workday Prism Analytics

Compared 4% of the time

Amazon QuickSight vs Workday Prism Analytics

Compared 4% of the time

Oracle Analytics Cloud vs Workday Prism Analytics

Compared 3% of the time

More Workday Prism Analytics Competitors

Product Reports

Buyer's Guide

Databricks

June 2025

Download Databricks product report

Buyer's Guide

BI (Business Intelligence) Tools

June 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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