Databricks vs VAST Data comparison

The compared Databricks and VAST Data solutions aren't in the same category. Databricks is ranked #8 in CDW , with an average rating of 8.3, and holds a 8.5% mindshare in the category. VAST Data is ranked #13 in N , and holds a 6.0% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of VAST Data users who would recommend it.

Databricks

Read 91 Databricks reviews

23,965 Views
2,157 Comparison Views

96% willing to recommend

VAST Data

Read 2 VAST Data reviews

5,196 Views
1,247 Comparison Views

100% willing to recommend

Databricks

VAST Data

Comparison Buyer's Guide

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Executive SummaryUpdated on Jul 27, 2025

Databricks and VAST Data compete in the data infrastructure landscape. Databricks leads in feature richness and integration, while VAST Data is preferred for storage efficiency and performance.

Features: Databricks offers a collaborative data processing environment, robust integration with Apache Spark, and supports machine learning applications. VAST Data focuses on cutting-edge storage solutions, advanced data protection, and high availability.

Ease of Deployment and Customer Service: Databricks provides a managed cloud deployment model, simplifying setup and scaling with efficient customer service. VAST Data offers an on-premises deployment for direct control with knowledgeable support addressing technical difficulties.

Pricing and ROI: Databricks has a subscription-based pricing model with flexible scaling and moderate upfront cost, optimizing value over time. VAST Data often involves higher initial expenditures due to hardware investments, leading to significant long-term ROI through efficient storage management.

To learn more, read our detailed Cloud Data Warehouse Report (Updated: July 2025).

Buyer's Guide

Cloud Data Warehouse

July 2025

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Helped 865,164 peers since 2012

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

Ranking in other categories

Cloud Data Warehouse (8th), Data Science Platforms (1st), Streaming Analytics (1st)

VAST Data

Average Rating

10.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

All-Flash Storage (32nd), File and Object Storage (18th), NVMe All-Flash Storage Arrays (13th)

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 8.5%, up 5.1% compared to last year.
VAST Data, on the other hand, focuses on NVMe All-Flash Storage Arrays, holds 6.0% mindshare, down 6.4% since last year.

Cloud Data Warehouse

NVMe All-Flash Storage Arrays

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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Alan Powers

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.

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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 solution is built from Spark and has integration with MLflow, which is important for our use case."

"The solution is very easy to use."

"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."

"The ability to stream data and the windowing feature are valuable."

"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."

"Databricks is a robust solution for big data processing, offering flexibility and powerful features."

"I think Databricks is very good at facilitating AI and machine learning projects; they implement AI and machine learning models very well, and clients can run their models on Databricks."

"It offers AI functionalities that assist with code management and machine learning processes."

More Databricks pros

"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

"I believe that this product could be improved by becoming more user-friendly."

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

"This solution only supports queries in SQL and Python, which is a bit limiting."

"I would love an integration in my desktop IDE. For now, I have to code on their webpage."

"Pricing is one of the things that could be improved."

"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."

"The solution has some scalability and integration limitations when consolidating legacy systems."

"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."

More Databricks cons

"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

"Databricks are not costly when compared with other solutions' prices."

"Price-wise, I would rate Databricks a three out of five."

"We're charged on what the data throughput is and also what the compute time is."

"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 licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."

"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."

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

"The pricing depends on the usage itself."

More Databricks pricing and cost advice

"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

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Computer Software Company

14%

Manufacturing Company

14%

Financial Services Firm

12%

University

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 ...

See all answers

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...

See all answers

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

Can you provide any information you may have on VAST Data?

Here are some technical details about VAST Data: VAST Data is a software-defined storage platform designed to scale to petabyte and exabyte levels. The platform uses a unique architecture that de...

See all answers

Comparisons

Dataiku vs Databricks

Compared 10% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Microsoft Azure Machine Learning Studio vs Databricks

Compared 2% of the time

More Databricks Competitors

NetApp AFF vs VAST Data

Compared 10% of the time

Dell PowerScale (Isilon) vs VAST Data

Compared 10% of the time

Pure Storage FlashBlade vs VAST Data

Compared 8% of the time

Qumulo vs VAST Data

Compared 8% of the time

MinIO vs VAST Data

Compared 7% of the time

More VAST Data Competitors

Product Reports

Buyer's Guide

Databricks

August 2025

Download Databricks product report

Buyer's Guide

NVMe All-Flash Storage Arrays

July 2025

Download VAST Data product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

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.

Databricks

Innovation to break decades of data storage trade-offs.

VAST Data

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, Microsoft, Google and others in Cloud Data Warehouse. Updated: July 2025.

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