Azure Databricks vs. IBM DataStage

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

Excellent Cloud data mapping tool and easy creating multiple project data analytics in real-time and the report distribution are excellent via this IBM product. Easy tool to provide data visualization and the integration is effective and helpful to migrating huge amounts of data across other platforms and different websites insights gathering.

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

• Very reliable in handling data extraction, data transformation and loading
• Flexibility in connecting to different type of databases, relational or non-relational
• Great features such as parallel processing, hash handling, etc.
• You can also take advantage of its FTP functions, and scheduling features if you need to.

Incentivized

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

Incentivized

• You must understand and know the algorithms, since the wrong use of them generates more time in processing.
• Metadata. You need to develop with connectors, and taking all the Metadata from the menu, all the data that you complete manually, you can't track it.

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

Because it is a flexible tool that can manage many flows and create a strong solution with a interesting use of variables. Easy to scale up as you can copy jobs arleady build and modify them. SQL queries allow to be fast in development and have the pushdown feature, but you loose a little of user friendly look. Metadata management is not strong as a visual feature, but can be determine by job codes.

Incentivized

It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.

Incentivized

IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.

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

No, it wasn’t my decision to use such an ETL product. I’m just the administrator at this point. I’ve heard there are other products there that are even on cloud support. That is much easier to use, more agile, and user-friendly. That doesn’t have that barrier from user to administrator to the developer standpoint.

• 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

• Not directly related to ROI or cost figures. Only comment here is that IBM tools tend to be more costly than average ETL tools, but it depends on if the company is an IBM shop.
• One positive aspect is the company has had not a need to switch ETL tool for years.
• Upgrading to newer versions of the tool brings flexibility in the tool and up-to-date features in relation to other applications.

Incentivized