Bonita Platform vs. Databricks Data Intelligence Platform vs. IBM InfoSphere Information Server

Well suited for low code/no code applications centered around approval flows. It has built-in task management for users to see their pending actions, comments, statuses, etc. It has a very nice design for process flows. Less appropriate may be for generic type applications with complex screens and logic within those screens that need a lot of data to process.

Incentivized

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

Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.

• Bonita seems particularly suited for processes requiring a great deal of human interaction. Its user model allows you to control access to business processes in a fine-grained way. This allows for business processes to move smoothly between users and services as the process advances.
• The definition and usage of custom forms from the latest version of Bonita seems particularly powerful. It allows for a thorough customization of the look-and-feel and does not require complex developments.
• The web interface and administration section have greatly improved in the latest versions. Installation and configuration of processes has become more flexible and more structured. The administration section gives a good view on failed processes, allowing to analyse problems in an efficient way.

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

• IIS best for ETL ,not ELT , and many and diffrent source systems.
• It also can process big data , unstuctured data
• It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems

Incentivized

• There is a learning curve beyond the boot camps that needs to be addressed with more structured curriculum.
• The full stack technologies are industry standard, but these [are] challenging to learn and could use a learning path and orientation. There's probably opportunity for third-parties here to help with learning and adoption.

Incentivized

• Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
• It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
• For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.

Incentivized

• I would be nice to have a new web development environment for DataStage.
• Connectivity Packs such as Pack for SAP Application are a little pricey.
• It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.

Incentivized

We just renewed our license

Incentivized

• Scale of implementation
• IBM techsupport

Incentivized

Bonita Platform has allowed us to develop GUI relatively fast using its UI Designer while being able to seamlessly integrate our business logic in Java in a BPMN2 process diagram. It gives a nice productivity boost but still requires programming know-how to be able to deliver the final solution to your business problems.

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

Engine itself is efficient enough for most cases I dealt with. It can also be extended by clustering. I have done performance tests with JMeter and only managed to induce the crash of... JMeter. If there are efficiency issues they usually concern bad design/implementation of created apps or bottlenecks in integrated systems. Although I have met two cases with efficiency loss.

1. Java 7 related PermGen saturation caused by big number of installed apps (there is no jar dependency reusal between apps option).

2. Big number of waiting event handlers in processes stresses the database.

Incentivized

It was sometimes difficult to get support on Bonita API.

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.

Nothing in particular

Incentivized

RHPAM is maybe a very good BPM process engine but is very limited to build a complete application.

We also try site soft W4 which needs more developments to build an application. We finally choose Bonita which is easier to get ready with.

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

DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS

Respect of BPMN standard over the long term. Good enhancements by Bonitasoft for new use cases, for example the introduction of a real form editor even if it has been technically difficult to manage. Once done though, we have far greater possibility of human interaction.

Incentivized

• Case management provided as better tracking which help us to meet SLAs.
• Auto email notification helps to address "Where are my request" answers which eventually increased our customer delight index.
• By using the third-party integration, we are able to provide visibility w.r.t end to end request status.

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

• Productivity of the development of integration processes.
• Better documentation and governance.
• Reduce training costs of various technologies.