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 setup was straightforward."
"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"The solution is very easy to use."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"It's easy to increase performance as required."
"The initial setup phase of Databricks was good."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"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."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"Databricks could improve in some of its functionality."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"I have seen better user interfaces, so that is something that can be improved."
"It's not easy to use, and they need a better UI."
"We'd like a more visual dashboard for analysis It needs better UI."
"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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