Databricks Data Intelligence Platform vs. IBM watsonx.data intelligence

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.

Incentivized

The IBM Watson Knowledge Catalog is most well suited for large companies. With large companies storing data for a long amount of time, this can be helpful to allow all team members to find documents with ease. It would be less appropriate for storage that is deleted very often or does not needs to be saved for long amounts of time.

Incentivized

• Process raw data in One Lake (S3) env to relational tables and views
• Share notebooks with our business analysts so that they can use the queries and generate value out of the data
• Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
• Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers

Incentivized

• Data discovery.
• Technical Data Lineage.
• Business Data Lineage.
• Data .
• Multiple Data Catalog Management.
• Creation of Governance Rules.
• Data Masking.

Incentivized

• 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

Incentivized

• I think an industry-specific data catalog service will be good.
• Effective alignment of IBM consulting services and bringing in an Industry point of view will be great.
• Effective reach out like roadshows, etc. will be good.

Incentivized

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

Incentivized

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.

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.

Incentivized

The IBM Watson Knowledge Catalog is a great amount of storage for the price. It is easily accessed by all users in the company. It provides great search features and clear pathways to locate documents. This is great for the team and our client when needing access to a specific document.

Incentivized

• The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
• DB has the ability to terminate/time out instances which helps manage cost.
• The ability to quickly access typical hard to build data scenarios easily is a strength.

Incentivized

• The negative note: is that it needs to have a very secure cloud infrastructure and with its data well defined for integration with other databases.
• The positive point: allows for quick data discoveries aiding a quick implementation of privacy programs.

Incentivized