Databricks vs Starburst Enterprise comparison

Databricks and Starburst are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.4, while Starburst is ranked #13 with an average rating of 8.5. Databricks holds a 14.5% mindshare in Data Science Platforms, compared to Starburst’s 2.2% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Databricks

Read 91 Databricks reviews

22,527 Views
9,912 Comparison Views

96% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,352 Views
1,109 Comparison Views

100% willing to recommend

Databricks

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Databricks and Starburst Enterprise are competing products in the data analytics platform category. Databricks seems to have the upper hand regarding ease of deployment and customer service, while Starburst Enterprise is favored for its features, justifying its cost.

Features: Databricks is known for its robust machine learning capabilities, seamless integration with various data sources, and strong collaboration features. Starburst Enterprise is recognized for its powerful query engine, broad compatibility with numerous data storage systems, and efficient handling of large datasets.

Ease of Deployment and Customer Service: Databricks offers a straightforward deployment process and reliable customer support that provides timely assistance. Starburst Enterprise may require more technical knowledge for deployment but offers scalability benefits. Its customer service is efficient but not as accessible as Databricks.

Pricing and ROI: Databricks generally offers lower setup costs and a high initial ROI due to its machine learning and data processing efficiency. Starburst Enterprise, with a higher initial cost, ensures a notable ROI through its advanced features for complex data environments.

To learn more, read our detailed Databricks vs. Starburst Enterprise Report (Updated: July 2025).

Buyer's Guide

Databricks vs. Starburst Enterprise

July 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

Ranking in Streaming Analytics

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th)

Starburst Enterprise

Ranking in Data Science Platforms

13th

Ranking in Streaming Analytics

16th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2025, in the Data Science Platforms category, the mindshare of Databricks is 14.5%, down from 19.8% compared to the previous year. The mindshare of Starburst Enterprise is 2.2%, up from 1.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	14.5%
Starburst Enterprise	2.2%
Other	83.3%

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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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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

"The ease of use and its accessibility are valuable."

"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."

"Databricks offers various courses that I can use, whether it's PySpark, Scala, or R."

"I would rate them ten out of ten."

"The processing capacity is tremendous in the database."

"The initial setup is pretty easy."

"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."

More Databricks pros

"It's very scalable, fast performing, and supports many catalogs."

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

Cons

"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."

"Databricks has a lack of debuggers, and it would be good to see more components."

"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 pricing of Databricks could be cheaper."

"The integration of data could be a bit better."

"The biggest problem associated with the product is that it is quite pricey."

"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."

"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."

More Databricks cons

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

"There should be support for REST API data sources to access data from the web."

Pricing and Cost Advice

"The pricing depends on the usage itself."

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

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

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

"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."

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

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

"The solution requires a subscription."

More Databricks pricing and cost advice

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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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

42%

Computer Software Company

Government

Retailer

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...

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 Starburst Enterprise?

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

See all answers

What needs improvement with Starburst Enterprise?

See all answers

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

See all answers

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Product Reports

Buyer's Guide

Databricks

September 2025

Download Databricks product report

Buyer's Guide

Data Science Platforms

August 2025

Download Starburst Enterprise product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

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

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

Starburst

Sample Customers

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

Information Not Available

Buyer's Guide

Databricks vs. Starburst Enterprise

July 2025

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