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 8.4, while TIBCO is ranked #24. Databricks holds a 9.6% mindshare in Data Science Platforms, compared to TIBCO’s 1.2% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Databricks

Read 92 Databricks reviews

18,651 Views
8,020 Comparison Views

96% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

588 Views
582 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: December 2025).

Buyer's Guide

Databricks vs. TIBCO Data Science

December 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 (9th), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)

TIBCO Data Science

Ranking in Data Science Platforms

24th

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Databricks is 9.6%, down from 18.9% compared to the previous year. The mindshare of TIBCO Data Science is 1.2%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	9.6%
TIBCO Data Science	1.2%
Other	89.2%

Data Science Platforms

Featured Reviews

SimonRobinson

Governance And Engagement Lead

Improved data governance has enabled sensitive data tracking but cost management still needs work

I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.

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JacekSierajewski

Tibco Spotfire Expert (contractor via Amaris) at GSK

Good performance, reporting, and data visualization

The two similar solutions that I have used are MicroStrategy and Tableau. Tableau is pretty similar and it would be difficult for me to point out the differences. With MicroStrategy, it has a great feature where you build the representation in the database and it then the tool creates SQL queries by itself. There are more differences between these tools but this is the one essential difference.

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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 has helped us have a good presence in data."

"I like cloud scalability and data access for any type of user."

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

"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."

"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."

"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."

"The most significant benefit Databricks has brought to my company is the Unity Catalog."

"I work in the data science field and I found Databricks to be very useful."

More Databricks pros

"The most valuable feature is the performance."

"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 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

"In the next release, I would like to see more optimization features."

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

"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."

"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."

"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."

"The API deployment and model deployment are not easy on the Databricks side."

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

"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."

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."

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

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

"The scripting for customization could be improved."

Pricing and Cost Advice

"We only pay for the Azure compute behind the solution."

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

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

"The solution is affordable."

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

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

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

"The solution is based on a licensing model."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

Healthcare Company

No data available

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 ...

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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...

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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

January 2026

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Buyer's Guide

Data Science Platforms

January 2026

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Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Alpine Data Chorus

Overview

Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.

Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.

What features make Databricks unique?

Notebook: Enables collaborative work among team members.
Delta Lake: Optimizes data management operations.
Unity Catalog: Provides governance over data assets.
Cloud Integration: Seamlessly connects with major cloud platforms.

What benefits can users expect from Databricks?

Versatility: Supports diverse applications in data science and engineering.
Performance: Delivers efficient handling of large-scale analytics tasks.
Collaboration: Enhances teamwork in data projects.
Unified Environment: Centralizes machine learning and analytics activities.

In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.

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

December 2025

Free Report: Databricks vs. TIBCO Data Science

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