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 #14 with an average rating of 8.5. Databricks holds a 17.2% 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 90 Databricks reviews

13,763 Views
10,002 Comparison Views

96% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,164 Views
994 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: April 2025).

Buyer's Guide

Databricks vs. Starburst Enterprise

April 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 (7th)

Starburst Enterprise

Ranking in Data Science Platforms

14th

Ranking in Streaming Analytics

12th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Data Science Platforms category, the mindshare of Databricks is 17.2%, down from 19.5% compared to the previous year. The mindshare of Starburst Enterprise is 2.2%, up from 1.6% 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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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

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

"It's great technology."

"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."

"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."

"The most valuable feature of Databricks is the integration with Microsoft Azure."

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

"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."

"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."

More Databricks pros

"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."

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

Cons

"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."

"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."

"The initial setup of Databricks could be complex."

"Would be helpful to have additional licensing options."

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

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

"This solution only supports queries in SQL and Python, which is a bit limiting."

"Databricks can improve by making the documentation better."

More Databricks cons

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

"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."

Pricing and Cost Advice

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

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"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 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."

"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."

"I rate the price of Databricks as eight out of ten."

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

"Databricks' cost could be improved."

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

44%

Computer Software Company

Energy/Utilities 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 ...

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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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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

Comparisons

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Compared 11% of the time

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Compared 9% of the time

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Compared 7% of the time

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Compared 7% of the time

KNIME vs Databricks

Compared 2% of the time

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Compared 16% of the time

Dremio vs Starburst Enterprise

Compared 14% of the time

Alteryx vs Starburst Enterprise

Compared 9% of the time

Apache Spark Streaming vs Starburst Enterprise

Compared 4% of the time

Informatica Data Engineering Streaming vs Starburst Enterprise

Compared 3% of the time

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Product Reports

Buyer's Guide

Databricks

May 2025

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Buyer's Guide

Data Science Platforms

May 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

April 2025

Free Report: Databricks vs. Starburst Enterprise

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