No more typing reviews! Try our Samantha, our new voice AI agent.

Databricks vs Starburst Enterprise comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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
94
Ranking in other categories
Cloud Data Warehouse (4th), Data Management Platforms (DMP) (5th)
Starburst Enterprise
Ranking in Data Science Platforms
16th
Ranking in Streaming Analytics
19th
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Science Platforms category, the mindshare of Databricks is 7.2%, down from 15.3% compared to the previous year. The mindshare of Starburst Enterprise is 1.7%, down from 2.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Databricks7.2%
Starburst Enterprise1.7%
Other91.1%
Data Science Platforms
 

Featured Reviews

SimonRobinson - PeerSpot reviewer
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.
KamleshPant - PeerSpot reviewer
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.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Databricks' Lakehouse architecture has been most useful for us, and the data governance has been absolutely efficient in between other kinds of solutions."
"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."
"I would rate them ten out of ten."
"I think the features I like the most are the scalability of the solution as well as its ability to share."
"It helps integrate data science and machine learning capabilities."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"Stability of the product is good, whether it's handling large volumes, diverse elements of data or processing data at speed."
"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."
"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

"Doesn't provide a lot of credits or trial options."
"I think the automatic categorization of variables needs to be improved; the current functionality is not always efficiently identifying the features of the data that is collected."
"The integration and query capabilities can be improved."
"The API deployment and model deployment are not easy on the Databricks side."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"The product needs samples and templates to help invite users to see results and understand what the product can do."
"Databricks has a lack of debuggers, and it would be good to see more components."
"The pricing is not the cheapest but it's understandable because it's a very high-end solution and easy to use, there's a lot of complexity masked away."
"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

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"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 product pricing is moderate."
"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
"The pricing depends on the usage itself."
"Databricks' cost could be improved."
"The cost is around $600,000 for 50 users."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"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."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
908,834 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
10%
Computer Software Company
6%
Healthcare Company
6%
Financial Services Firm
33%
Computer Software Company
8%
Manufacturing Company
6%
Construction Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business26
Midsize Enterprise12
Large Enterprise58
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 ...
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...
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...
What needs improvement with Starburst Enterprise?
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 ...
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...
What advice do you have for others considering Starburst Enterprise?
Starburst requires a heavy investment in infrastructure; it needs heavy computing and storage. If your use case doesn't involve heavy processing or storage, then Starburst might not be the solution...
 

Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
No data available
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Information Not Available
Find out what your peers are saying about Databricks vs. Starburst Enterprise and other solutions. Updated: June 2026.
908,834 professionals have used our research since 2012.