Boomi vs. Databricks Data Intelligence Platform

Legacy systems often need to be replaced or integrated with new applications in order to modernize businesses. A strong API strategy that avoids custom coding and third-party programs is essential to enable this integration. Boomi's new-age connectivity and integration solutions ensure safe, secure, and robust integration. In the age of information, businesses are under more pressure than ever to be able to collect and manage large amounts of data. This data comes in from a variety of sources, including personalized devices such as voice assistants and wearable tech. While this data can be immensely valuable to businesses, they often lack the infrastructure necessary to handle it effectively. This can lead to data build-up in databases or silos, and can eventually lead to problems with integration and security.

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

• Pre-built connectors to almost anything which greatly reduce time to release of your integration needs.
• Easy to use development platform with drag&drop features. Non-technical people could build simple integration processes in no time.
• Great user community where you can get quick help if needed. Boomi people hang around there a lot.

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

• More from a development perspective. It is always difficult to use the properties features. It takes a while to understand how the data/variables can be used across an integration.
• Dell Boomi should also invest more on API Management and not just seen as a ETL,ESB tool.
• Should roll out features more often based on users reviews.

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

Dell Boomi has provided us with the ability to connect our campus together using our various existing platforms. There are many supported features and have yet to run into something that we cannot do. Its user interface is very intuitive which would allow users to begin developing fairly easily. There is a myriad of resources available

Incentivized

My IT and Finance teams have noted that setting up the tool is a breeze. Dell Boomi has never caused an issue during a system implementation that I am aware of. We are pleased with the tool and recommend others consider it.

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

The atom sphere takes a time to load, when I open a process or when I open a log. One more slow processing is when I import objects from NetSuite.

About the performance of processing, it looks like Boomi takes a time to initialize some things such as connectors before starting the process. This is also performance we have.

Incentivized

Boomi support was responsive and knowledgable, however being a closed cloud service, it doesn't have good community support. We found the learning curve to be steep and there aren't avenues like google, forums, or blogs that provide community driven insight into the product or how to go about designing solutions using the tool

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.

We decided to go with Dell Boomi because another department in our company was already using the software. We did not research competitor applications to use as our business solution. Dell Boomi was very easy and quick to set up, so once we decided to use Dell Boomi for systems integration, we had it set up and running within a few working days.

Incentivized

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

• It has allowed us to scale significantly without having to add headcount, specifically those geared towards data entry. We went from a $10m ARR business to $200m ARR business with the same amount of Order Processors and 12x amount of transactions by leveraging Boomi to perform a lot of the work, and then having the Order Processing team to simply review that the transaction was processed successfully.

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