Databricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.
$0.07
Per DBU
Unity
Score 9.4 out of 10
N/A
Unity Technologies headquartered in San Francisco offers the Unity real-time 3D and 2D development platform.
Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
Unity is excellent for 2D and 3D games and educational experiences. It is well-suited for VR and AR development. It is also a great platform for mobile games. It is less-suited for non-game purposes (although it can certainly be used for those as well), or educational experiences. It is also less-suited for AR experiences that are highly complex, where you will probably want to write the native code in Android Studio or Xcode, as the case may be. It is theoretically less-suited for cases where performance is a huge concern as well, although, in my experience, performance has never been a problem.
Unity is a multiplatform game engine. It has more than 20 options for exporting your game, ranging from desktop, mobile, console, web and, lately, VR and AR. Unity was one of the first game engines able to export games playable on internet browsers and it helped to cement the World Wide Web as a place fit for gaming.
Unity has a very smooth learning curve for beginners. It is easy to start and soon you are seeing some tangible results of your efforts. The game engine has all sorts of helpers and shortcuts to facilitate some frequent tasks in game development.
Another of Unity's advantage is the access to Assets Store from within the game engine, allowing the user to import instantly objects, scripts and textures from the store into their projects. Such easy access to these elements from inside a project greatly enhances speed production and is particularly helpful to beginners.
Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
Visualization in MLFLOW experiment can be enhanced
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.
in terms of graph generation and interaction it could improve their UI and UX
It's actually incredibly easy to use given the complex tasks you have. Once you learn the various windows it becomes second nature. Compared to something like Blender (which I would probably rate as a 2 on usability), the learning curve of Unity is a breeze! The only improvements I can think of would be to streamline some common workflows so you don't have to dig through menus to find them.
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
I have not had to use Unity's support extensively. This is likely because there is so much documentation and so many classes available for free online. Due to this, there is little need for support. They were very responsive when I requested educational licensing. Setting it up and providing it all quickly.
The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
We love utilizing unreal engines but we seem to have a better use case for the architectural visualization side of things. This has given us the ability to find better more photo-realistic assets from not only the marketplace but 3rd party sites that have a unity bases file to work off of.
