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 8.3, while Starburst is ranked #14 with an average rating of 8.5. Databricks holds a 19.1% mindshare in Data Science Platforms, compared to Starburst’s 2.1% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Databricks

Read 85 Databricks reviews

17,588 Views
11,896 Comparison Views

96% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,282 Views
1,140 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: January 2025).

Buyer's Guide

Databricks vs. Starburst Enterprise

January 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

No ranking in other categories

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 January 2025, in the Data Science Platforms category, the mindshare of Databricks is 19.1%, up from 18.5% compared to the previous year. The mindshare of Starburst Enterprise is 2.1%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Parag Bhosale

Senior Data Engineer at a logistics company with 51-200 employees

Integrating engineering and learning, but cost challenges arise with cluster management

We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller. We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly. We need to stay in sync with the DVR versions, and migrations can pose challenges. For example, issues arose when we moved a cluster from a previous version to the latest one. We could use their job clusters, however, that increases costs, which is challenging for us as a startup. Maintaining this infrastructure can be a headache.

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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

"The tool helps with data processing and analytics with large-scale data or big data since it is associated with managing data at a large scale."

"It's easy to increase performance as required."

"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 solution offers a free community version."

"The setup is quite easy."

"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."

"Databricks helps crunch petabytes of data in a very short period of time."

"The main features of the solution are efficiency."

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

"The tool should improve its integration with other products."

"There should be better integration with other platforms."

"Implementation of Databricks is still very code heavy."

"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

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

"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."

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

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

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

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

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

"The billing of Databricks can be difficult and should improve."

"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 based on a licensing model."

"The solution requires a subscription."

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."

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

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

43%

Computer Software Company

10%

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...

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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...

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

Comparisons

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Compared 11% of the time

Informatica PowerCenter vs Databricks

Compared 8% of the time

Dremio vs Databricks

Compared 8% of the time

Amazon SageMaker vs Databricks

Compared 8% of the time

Microsoft Power BI vs Databricks

Compared 7% of the time

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Dremio vs Starburst Enterprise

Compared 22% of the time

Starburst Galaxy vs Starburst Enterprise

Compared 21% of the time

Alteryx vs Starburst Enterprise

Compared 14% of the time

Apache Spark Streaming vs Starburst Enterprise

Compared 4% of the time

Confluent vs Starburst Enterprise

Compared 3% of the time

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Product Reports

Buyer's Guide

Databricks

January 2025

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Buyer's Guide

Data Science Platforms

January 2025

Download Starburst Enterprise product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

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Databricks

Starburst

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.

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.

Sample Customers

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

Information Not Available

Buyer's Guide

Databricks vs. Starburst Enterprise

January 2025

Free Report: Databricks vs. Starburst Enterprise

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