Databricks vs TIBCO Data Science comparison

Databricks and TIBCO are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.3, while TIBCO is ranked #25. Databricks holds a 16.5% mindshare in Data Science Platforms, compared to TIBCO’s 0.6% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Databricks

Read 91 Databricks reviews

12,650 Views
7,192 Comparison Views

96% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

339 Views
124 Comparison Views

100% willing to recommend

Databricks

TIBCO Data Science

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Databricks and TIBCO Data Science compete in the data science and analytics space. Databricks appears to have an advantage in scalability and collaborative features, whereas TIBCO Data Science is favored for its comprehensive analytics and integration capabilities.

Features: Databricks offers collaborative features, seamless integration with data sources, and strong machine learning capabilities. TIBCO Data Science focuses on providing analytics options, real-time insights, and robust integration within enterprise environments.

Room for Improvement: Databricks could improve integration with enterprise systems, offer more advanced analytics options, and enhance its real-time data processing capabilities. TIBCO Data Science may need to work on reducing deployment time, improving its cost-effectiveness, and offering more agile scaling options.

Ease of Deployment and Customer Service: Databricks provides a cloud-based deployment model that allows quick setup and flexible scaling, with a responsive customer support system. TIBCO Data Science offers both on-premise and cloud-deployment models with robust integration with enterprise systems, which may require more initial setup time, along with dedicated service support.

Pricing and ROI: Databricks presents a flexible pricing model with lower initial setup costs, focusing on delivering improved ROI through scalability. TIBCO Data Science may involve higher initial investment but delivers high ROI for companies needing comprehensive data solutions, potentially offering greater long-term value for complex data needs.

To learn more, read our detailed Databricks vs. TIBCO Data Science Report (Updated: June 2025).

Buyer's Guide

Databricks vs. TIBCO Data Science

June 2025

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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

Ranking in Data Science Platforms

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (8th), Streaming Analytics (1st)

TIBCO Data Science

Ranking in Data Science Platforms

25th

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Science Platforms category, the mindshare of Databricks is 16.5%, down from 19.7% compared to the previous year. The mindshare of TIBCO Data Science is 0.6%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

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.

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Veeresh-SHRINGARI

Portfolio Manager, AI & ML at a healthcare company with 10,001+ employees

A straightforward initial setup and good reporting but needs better documentation

It would be ideal if it could be put onto the NMP where you can make more of an analysis. Right now, people don't have enough time to go through the report and make an analysis. It should provide the information of what is on the report into some kind of a dialogue form. Then, a person can ask certain questions and it could interactively give the required report. In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues. If you are doing certain operations of RDBMS, you suffer in terms of the latency of the data. That can be improved upon. Users should be able to cross tables of the web pages they are developing on Spotfire and this needs to be really easy and convenient. Right now, you need to do a lot of tweaks. The solution should be more user-friendly and require fewer tweaks, extensions, and workarounds.

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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' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."

"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."

"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."

"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."

"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."

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

"Its lightweight and fast processing are valuable."

More Databricks pros

"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."

"The most valuable feature is the performance."

"The idea that you don't have to generate reports each day but they are sent automatically is great."

"The most valuable feature is the ease of setting up visualizations."

Cons

"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."

"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."

"The integration and query capabilities can be improved."

"The connectivity with various BI tools could be improved, specifically the performance and real time integration."

"There are no direct connectors — they are very limited."

"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."

"There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files."

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

More Databricks cons

"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."

"I would like the visualization for the map of countries to be more easily configurable."

"Additional templates would help to get things moving more quickly in terms of getting the reports out."

"The scripting for customization could be improved."

Pricing and Cost Advice

"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."

"It is an expensive tool. The licensing model is a pay-as-you-go one."

"I would rate the tool’s pricing an eight out of ten."

"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."

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

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

More Databricks pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

No data available

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 ...

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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...

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Product Reports

Buyer's Guide

Databricks

June 2025

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Buyer's Guide

Data Science Platforms

June 2025

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Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Alpine Data Chorus

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

TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.

TIBCO

Sample Customers

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

Havas Media, Tipping Point Community, eviCore

Buyer's Guide

Databricks vs. TIBCO Data Science

June 2025

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