Azure Databricks vs. IBM Cloud Pak for Data

Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives.

Incentivized

Unlike others analytics tool IBM Cloud Pak for Data provides out-of-the-box privacy, model interpretability and fairness monitoring, along with automatic explanation of data and models written in business language. It's a great tool that all business should emulate. Great user experience because of every feature is functional and improved constantly.

Incentivized

• Consistently great performance when dealing with huge scale data with the help of spark architecture
• Magic commands such as spark sql, pyspark, scala . This comes really handy in day to day work
• Integration with other Azure services is super smooth and robust

Incentivized

• The AI services catalog like the Watson Assistant is very good.
• The analytics dashboard featuring all the recent history is very good with IBM.
• Searching for data through the unified search option is super cool.

Incentivized

• Intuitive interface
• Ease of use
• Providing FAQ or QRGs

Incentivized

• It is complex; The platform comes with several features from MLOPs to Customer 360 which may take a long time for the user to understand.

Incentivized

Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!

Incentivized

Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse

Incentivized

IBM has healing mechanisms when resource usage is high. This platform performs well, but when it runs out of capacity, it has crashed for many clients. This is innate in its original design

Incentivized

• The support team is amazing, they help you at every stage of the projects, from sales to delivery.
• On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
• There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform

Incentivized

• can improve readiness for cloud migration, improve licensing flexibility with IBM, and reduce both hardware purchases and infrastructure management efforts.
• reduces the expenses of internal resources.
• should improve efficiencies, reduce risks, and increase performance

Incentivized