We compared Databricks and VAST Data based on our users reviews in five parameters. After reading the collected data, you can find our conclusion below:
Comparison Results: Databricks is known for its complexity during initial setup, especially regarding database and third-party components. VAST Data stands out for its simple and efficient setup, which can be completed in less than a day. Regarding features, Databricks offers a comprehensive range of functionalities such as stream events, automated cluster creation, and universal data access. It is also commendable in managing large datasets and provides language flexibility. On the other hand, VAST Data excels in failover capability, resiliency, and encryption. Opinions on pricing for Databricks vary, with some considering it expensive while others find it reasonably priced. VAST Data falls in the middle category in terms of pricing, setup cost, and licensing. Customer service and support for both platforms have generally positive feedback. Databricks provides good technical support, and VAST Data is highly regarded for its prompt and efficient assistance with quick response times. To summarize, Databricks offers a wide range of functionalities and flexibility, while VAST Data is valued for its simplicity, efficiency, and failover capability.
"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The initial setup phase of Databricks was good."
"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."
"It can send out large data amounts."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."
"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."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"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."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"There is room for improvement in visualization."
"It should have more compatible and more advanced visualization and machine learning libraries."
"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."
"CI/CD needs additional leverage and support."
"The tool should improve its integration with other products."
"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."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while VAST Data is ranked 8th in NVMe All-Flash Storage Arrays with 2 reviews. Databricks is rated 8.2, while VAST Data is rated 10.0. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of VAST Data writes "Stability-wise, a device that has been up and running for years". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio, whereas VAST Data is most compared with Pure Storage FlashBlade, NetApp AFF, Pure Storage FlashArray, Qumulo and Red Hat Ceph Storage.
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