Bonita Platform vs. Databricks Data Intelligence Platform vs. Teradata Vantage

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

Teradata Vantage is well suited for large scale ETL pipelines like the ones we developed for anti money laundering risk matrices. It handles heavy joins, aggregations, and transformations on transactional data efficiently. We generate alert variables, adjust for inflation, and monitor establishments monthly with it, all integrated with Python and Control-M for a centralised automation across the company. For less appropriate, I would say that heavy resource demands might slow down experimentation for iterative work.

• 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

• ETL (Extract - Transfor - Load)
• NOS to send data from Teradata Vantage to S3 and from S3 to Teradata Vantage
• Teradata GeoSpacial feature
• Bulk reading and writing in huge tables
• MPP capacity already mature
• Temporal Capacity more mature that other solutions
• TASM

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

• Teradata is an excellent option but only for a massive amount of data warehousing or analysis. If your data is not that big then it could be a misfit for your company and cost you a lot. The cost associated is quite extensive as compared to some other alternative RDBMS systems available in the market.
• Migration of data from Teradata to some other RDBMS systems is quite painful as the transition is not that smooth and you need to follow many steps and even if one of them fails. You need to start from the beginning almost.
• Last but not least the UI is pretty outdated and needs a revamp. Though it is simple, it needs to be presented in a much better way and more advanced options need to bee presented on the front page itself.

Incentivized

We just renewed our license

Incentivized

Teradata is a mature RDBMS system that expands its functionality towards the current cloud capabilities like object storage and flexible compute scale.

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

Teradata Vantage allows us to create a scalable infrastructure to support our strategic initiatives. The dedicated compute power ensures reliable performance with isolated workloads and dedicated resources, optimizing workflows for faster, more efficient data transfers. The compute clusters support ETL processes and OSF’s developers and data science team with the flexibility to create self-service analytics, to spin up/down at any time, driving better performance and minimizing costs.

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.

We have meetings at the beginning with the technical team to explain our requirements to them and they were really putting in a lot of effort to come up with a solution which will address all our needs. They implemented the software and also trained a few of our resources on the same too. We can get in touch with them now as well whenever we run into a roadblock but it's very less now.

Incentivized

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

Teradata is way ahead of its competitor because of its unique features of ensuring data privacy and data never gets corrupted even in worst case scenario. In most cases, the data corruption is a major issue if left unused and it leads to important data being wiped off which in ideal case should be stored for 3 years

Incentivized

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

• Moving to Teradata in the Cloud-enabled a level of agility that previously didn't exist in the organization. It also enabled a level of analytic competency that was not achievable using other options on the aggressive timeline that was required. We didn't want to settle for reinventing a wheel when we had a super tuned performance capable beast readily available in Teradata. Teradata lets us focus on our business rather than spending money and effort trying to design software or database foundations features on an open source or lower performance platform.

Incentivized