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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 (30th), File and Object Storage (18th), 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 9.7%, up 9.1% compared to last year.
VAST Data, on the other hand, focuses on NVMe All-Flash Storage Arrays, holds 6.1% mindshare, up 5.9% since last year.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Databricks9.7%
Snowflake15.1%
Teradata8.8%
Other66.4%
Cloud Data Warehouse
NVMe All-Flash Storage Arrays Mindshare Distribution
ProductMindshare (%)
VAST Data6.1%
Dell PowerStore14.6%
NetApp AFF12.1%
Other67.2%
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

"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."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Databricks allowed us to go from non-existent insights (because the datasets were just too large) to immediate and rich insights once the datasets were ingested into our PySpark notebooks."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"Databricks is a robust solution for big data processing, offering flexibility and powerful features."
"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."
"Databricks has a scalable Spark cluster creation process, and the creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."
"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

"Databricks is still having some stability issues."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"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."
"The integration of data could be a bit better."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"Databricks should have more libraries for predictive analysis and machine learning. It should have more compatible and more advanced visualization and machine learning libraries."
"Databricks could improve in some of its functionality."
"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 am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
"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."
"The solution is a good value for batch processing and huge workloads."
"The solution is based on a licensing model."
"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."
"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."
"The solution requires a subscription."
"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
18%
Manufacturing Company
10%
Computer Software Company
7%
Healthcare Company
5%
Financial Services Firm
14%
Manufacturing Company
12%
Computer Software Company
10%
Healthcare Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business27
Midsize Enterprise12
Large Enterprise57
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...
Ask a question
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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: June 2026.
900,644 professionals have used our research since 2012.