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Databricks vs VAST Data comparison

 

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) (5th), 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 (10th)
 

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 8.9% compared to last year.
VAST Data, on the other hand, focuses on NVMe All-Flash Storage Arrays, holds 5.9% mindshare, down 6.0% since last year.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Databricks9.5%
Snowflake15.3%
Teradata8.7%
Other66.5%
Cloud Data Warehouse
NVMe All-Flash Storage Arrays Mindshare Distribution
ProductMindshare (%)
VAST Data5.9%
Dell PowerStore13.8%
NetApp AFF11.0%
Other69.3%
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's easy to increase performance as required."
"Databricks helps crunch petabytes of data in a very short period of time."
"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."
"It is fast, it's scalable, and it does the job it needs to do."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"It's very simple to use Databricks Apache Spark."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"There are good features for turning off clusters."
"The solution is useful for machine learning and scientific applications, including computer simulations."
"This has been one of the most reliable storage systems that I have ever used."
 

Cons

"The cost of this solution is high, on the expensive side."
"Costs can quickly add up if you don't plan for it."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."
"The first deployment is difficult. It is not straightforward and you have to think about a lot of stuff."
"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."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"The write performance could be improved because it is less than half of the read performance."
"The read/write ratio is an area in the solution with some flaws and needs improvement."
 

Pricing and Cost Advice

"I would rate Databricks' pricing seven out of ten."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"The pricing depends on the usage itself."
"I would rate the tool’s pricing an eight out of ten."
"The product pricing is moderate."
"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
"The solution requires a subscription."
"We acquired VAST Data as a one-time, capital purchase."
"Price-wise, VAST Data is not the cheapest, not the most expensive one."
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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
11%
Computer Software Company
9%
Healthcare Company
6%
 

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...
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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: July 2026.
908,800 professionals have used our research since 2012.