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 simplicity of development is the most valuable feature."
"The integration with Python and the notebooks really helps."
"It's easy to increase performance as required."
"Databricks' most valuable feature is the data transformation through PySpark."
"The solution is very easy to use."
"Its lightweight and fast processing are valuable."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"The ability to stream data and the windowing feature are valuable."
"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."
"Can be improved by including drag-and-drop features."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"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 product should provide more advanced features in future releases."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"Anyone who doesn't know SQL may find the product difficult to work with."
"Would be helpful to have additional licensing options."
"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."
"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."
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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