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Databricks vs VAST Data comparison

Why PeerSpot?
 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 8, 2026

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
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (4th), Data Science Platforms (1st), Data Management Platforms (DMP) (3rd), Streaming Analytics (1st)
VAST Data
Average Rating
10.0
Reviews Sentiment
7.5
Number of Reviews
2
Ranking in other categories
All-Flash Storage (28th), File and Object Storage (19th), NVMe All-Flash Storage Arrays (9th)
 

Mindshare comparison

Databricks and VAST Data aren’t in the same category and serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 9.5%, up 8.7% compared to last year.
VAST Data, on the other hand, focuses on NVMe All-Flash Storage Arrays, holds 5.9% mindshare, down 5.9% since last year.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Databricks9.5%
Snowflake15.4%
Teradata8.9%
Other66.2%
Cloud Data Warehouse
NVMe All-Flash Storage Arrays Mindshare Distribution
ProductMindshare (%)
VAST Data5.9%
Dell PowerStore13.3%
NetApp AFF10.5%
Other70.3%
NVMe All-Flash Storage Arrays
 

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.
Alan Powers - PeerSpot reviewer
HPC CTO at a manufacturing company with 10,001+ employees
Stability-wise, a device that has been up and running for years
The failover capability and resiliency are some of the solution's valuable features. The big thing is resilience because it has richer coding in it, so multiple devices can't fail. Also, one can still access a number of CBoxes that can allow one to access their file system. Once a device fails, it fails the transparency of the end-user, and it just starts using another resource. The encryption capability, the snapshots, along with a whole bunch of features make the tool valuable. VAST Data keeps adding more and more features all the time.

Quotes from Members

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

Pros

"It is a cost-effective solution."
"The initial setup of Databricks is straightforward and simple."
"The solution is very simple and stable."
"Stability of the product is good, whether it's handling large volumes, diverse elements of data or processing data at speed."
"Databricks' Lakehouse architecture has been most useful for us, and the data governance has been absolutely efficient in between other kinds of solutions."
"I work in the data science field and I found Databricks to be very useful."
"I don't think you can find any other tool or any other service that is faster than Databricks."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"This has been one of the most reliable storage systems that I have ever used."
"The solution is useful for machine learning and scientific applications, including computer simulations."
 

Cons

"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"Would be helpful to have additional licensing options."
"So far, we're not measuring any return on investment, such as saving time, money, or resources with Databricks."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"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 data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"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."
"The read/write ratio is an area in the solution with some flaws and needs improvement."
"The write performance could be improved because it is less than half of the read performance."
 

Pricing and Cost Advice

"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."
"I would rate Databricks' pricing seven out of ten."
"The billing of Databricks can be difficult and should improve."
"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."
"Price-wise, I would rate Databricks a three out of five."
"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."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"Price-wise, VAST Data is not the cheapest, not the most expensive one."
"We acquired VAST Data as a one-time, capital purchase."
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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
14%
Manufacturing Company
10%
Computer Software Company
8%
Outsourcing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business26
Midsize Enterprise12
Large Enterprise60
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...
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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
Norwest Venture Partners, General Dynamics Information Technology, Ginkgo Bioworks
Find out what your peers are saying about Snowflake Computing, Teradata, Google and others in Cloud Data Warehouse. Updated: September 2026.
913,683 professionals have used our research since 2012.