Databricks Data Intelligence Platform

What differentiates Databricks Data Intelligence Platform from other similar products?

Databricks is great for coders, and an excellent solution for large volumes of data. The interface needs usability improvements, but the learning curve is reasonably straightforward. It is well suited for automation and well suited for writing code. PySpark is an excellent language to learn and it works very fast.

What is your favorite aspect of this product?

It is an excellent tool for large volumes of data. It allows real-time virtualization and some very important automation. It integrates other technologies like Python, Spark and SQL.

What do you dislike most about this product?

Needs to improve in usability, visualization and collaboration features within teams. They also need to improve data presentation capabilities, graphs and visualizations and error messages.

What recommendations would you give to someone considering this product?

It's a great and promising technology. It is a highly adaptable solution for data engineering, data science and AI.

What differentiates Databricks Data Intelligence Platform from other similar products?

Ability to process massive amount of data up to several TB. It's ability to interface with cloud enhances its volumetric to a huge extent.

What is your favorite aspect of this product?

It's ability to support Big Data needs. With the volume of data growing day to day, the ability of this tool to process several TB within a few minutes is a distinguishing feature. It supports several Machine Learning models for Artificial Intelligence.

What do you dislike most about this product?

It is difficult to regenerate the existing tables when there is loss of internet and cloud connection. Also, Databricks has discouraging analytical tools in terms of analytics and dashboard options. Databricks is bad in terms of optimization of CPUs when dealing with datacenters,

What recommendations would you give to someone considering this product?

Good product to consider when dealing with data processing needs. However, if you want to build analytics/dashboard alone, evaluate other tools.

What differentiates Databricks Data Intelligence Platform from other similar products?

Native support in R, Scala, Python or SQL interface. Excellent provision of a map-reduce system for seamless distributed computing. Truly hides the details of a distributed architecture and allows developers to focus on the business logic as opposed to minor implementation details. Great for machine learning with large datasets.

What is your favorite aspect of this product?

Might be trivial, but the Jupyter notebook-like UI is extremely fruitful for explainable and maintainable code experiments. Great tool for collaboration with distributed systems optimizing a data intense pipeline.

What do you dislike most about this product?

I believe the tutorials and documents could be made more user-friendly. The initial stage of adaptation was a little slow due to the lack of information in some advanced but useful features on Databricks.

What recommendations would you give to someone considering this product?

I suggest starting with developing an end-to-end pipeline unrelated to your immediate project in order to get a hang of the product and the nuances. Going through the official tutorials on YouTube would definitely help as well, especially in terms of differentiating databricks from its competition or other products you may be considering. Since here they aren't trying to sell you the product, but exploring it to explain its usage.