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.
"We have the ability to scale, collaborate and do machine learning."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"The time travel feature is the solution's most valuable aspect."
"The technical support is good."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"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."
"There are no direct connectors — they are very limited."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"Doesn't provide a lot of credits or trial options."
"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."
"A lot of people are required to manage this solution."
"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."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"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 Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas VAST Data is most compared with Pure Storage FlashBlade, NetApp AFF, Pure Storage FlashArray, Qumulo and NetApp FAS Series.
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