Databricks vs VAST Data comparison

The compared Databricks and VAST Data solutions aren't in the same category. Databricks is ranked #7 in CDW , with an average rating of 8.3, and holds a 8.4% mindshare in the category. VAST Data is ranked #8 in N , with an average rating of 10.0, and holds a 5.8% 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 88 Databricks reviews

2,196 Views
1,662 Comparison Views

96% willing to recommend

VAST Data

Read 2 VAST Data reviews

1,266 Views
943 Comparison Views

100% willing to recommend

Databricks

VAST Data

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 12, 2025

Databricks and VAST Data compete in data processing and storage. Databricks stands out for analytics and AI, while VAST Data leads in storage performance.

Features: Databricks offers a unified platform for big data analytics, robust AI-driven capabilities, and supports collaborative workspaces. VAST Data provides high-speed file and object storage, emphasizes data durability, and enhances data accessibility for large datasets.

Ease of Deployment and Customer Service: VAST Data emphasizes an easy deployment process and strong customer support. Databricks offers solid integration capabilities but may require more technical expertise during setup. VAST Data is known for responsive support.

Pricing and ROI: Databricks has a competitive setup cost with favorable ROI for data analytics and offers scalable options. VAST Data involves a larger initial investment but ensures significant ROI through enhanced data management and cost savings. Databricks is suitable for budget-conscious firms, while VAST Data provides value for those focusing on robust storage solutions.

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

Buyer's Guide

Cloud Data Warehouse

March 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

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th), 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 (20th), File and Object Storage (9th), NVMe All-Flash Storage Arrays (8th)

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 8.4%, up 3.2% compared to last year.
VAST Data, on the other hand, focuses on NVMe All-Flash Storage Arrays, holds 5.8% mindshare, down 6.7% 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

"Databricks is a scalable solution. It is the largest advantage of the solution."

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

"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."

"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."

"I haven't heard about any major stability issues. At this time I feel like it's stable."

"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."

"In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."

"The solution is very easy to use."

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

"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."

"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."

"There should be better integration with other platforms."

"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."

"The API deployment and model deployment are not easy on the Databricks side."

"It would be very helpful if Databricks could integrate with platforms in addition to Azure."

"The initial setup is difficult."

"I have seen better user interfaces, so that is something that can be improved."

More Databricks cons

"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

"The price is okay. It's competitive."

"The cost is around $600,000 for 50 users."

"Databricks uses a price-per-use model, where you can use as much compute as you need."

"There are different versions."

"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."

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

"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."

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

11%

Manufacturing Company

Healthcare Company

Computer Software Company

16%

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

What do you like most about VAST Data?

The solution is useful for machine learning and scientific applications, including computer simulations.

See all answers

What is your experience regarding pricing and costs for VAST Data?

Price-wise, VAST Data is not the cheapest, not the most expensive one.

See all answers

What needs improvement with VAST Data?

The read/write ratio is an area in the solution with some flaws and needs improvement.

See all answers

Comparisons

Dataiku vs Databricks

Compared 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Dremio vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Amazon QuickSight vs Databricks

Compared 2% of the time

More Databricks Competitors

Pure Storage FlashBlade vs VAST Data

Compared 11% of the time

Dell PowerScale (Isilon) vs VAST Data

Compared 10% of the time

NetApp AFF vs VAST Data

Compared 10% of the time

Qumulo vs VAST Data

Compared 9% of the time

Snowflake vs VAST Data

Compared 7% of the time

More VAST Data Competitors

Product Reports

Buyer's Guide

Databricks

March 2025

Download Databricks product report

Buyer's Guide

NVMe All-Flash Storage Arrays

March 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: March 2025.

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