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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

"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"It is a cost-effective solution."
"The solution is very easy to use."
"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 solution is very simple and stable."
"The capability of the product is quite good and we are very satisfied with it overall."
"The most valuable feature is the versatility of the ecosystem."
"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"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

"There would also be benefits if more options were available for workers, or the clusters of the two points."
"The integration features could be more interesting, more involved."
"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 solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"Databricks does not always have clear updates. Often we find an update in the tool but we are not really sure what has changed."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"Databricks could improve in some of its functionality."
"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."
"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 do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"There are different versions."
"The price of Databricks is reasonable compared to other solutions."
"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."
"The solution is based on a licensing model."
"The billing of Databricks can be difficult and should improve."
"The solution is a good value for batch processing and huge workloads."
"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
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.
908,877 professionals have used our research since 2012.