Aurea Process (formerly CX Process) from Aurea Software in Austin is a business process management offering, based on Savvion BPM.
$200,000
per year
Databricks Data Intelligence Platform
Score 8.8 out of 10
N/A
Databricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.
$0.07
Per DBU
Pricing
Aurea Process
Databricks Data Intelligence Platform
Editions & Modules
License
$200,000
per year
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
Offerings
Pricing Offerings
Aurea Process
Databricks Data Intelligence Platform
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Aurea Process
Databricks Data Intelligence Platform
Features
Aurea Process
Databricks Data Intelligence Platform
Reporting & Analytics
Comparison of Reporting & Analytics features of Product A and Product B
Aurea Process
5.3
1 Ratings
38% below category average
Databricks Data Intelligence Platform
-
Ratings
Dashboards
6.01 Ratings
00 Ratings
Standard reports
6.01 Ratings
00 Ratings
Custom reports
4.01 Ratings
00 Ratings
Process Engine
Comparison of Process Engine features of Product A and Product B
Aurea Process
5.8
1 Ratings
36% below category average
Databricks Data Intelligence Platform
-
Ratings
Process designer
6.01 Ratings
00 Ratings
Process simulation
7.01 Ratings
00 Ratings
Business rules engine
5.01 Ratings
00 Ratings
SOA support
5.01 Ratings
00 Ratings
Process player
7.01 Ratings
00 Ratings
Model execution
5.01 Ratings
00 Ratings
Collaboration
Comparison of Collaboration features of Product A and Product B
Aurea Process
4.0
1 Ratings
70% below category average
Databricks Data Intelligence Platform
-
Ratings
Social collaboration tools
4.01 Ratings
00 Ratings
Content Management Capabilties
Comparison of Content Management Capabilties features of Product A and Product B
The tool has potential. Its capabilities and visual aspects could be considered rather basic but this might improve, particularly if the business intelligence/analytics aspect is leveraged. Once running well, it could allow (perhaps smaller) companies to successfully improve their customers' experiences through digitalizing customer journey - and we all know that customer loyalty goes a long way. However, whether or not the tool is comprehensive enough to deliver this for larger companies with more complex, multi- and omni-channel interactions is yet to be seen...
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.
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
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.
As our customers vary in size and maturity, the ROI ranges accordingly.
For younger, smaller businesses this is a useful tool. Digitalization of he customer journey has certainly helped save time and efforts in many cases.
For more mature market players the tool is not always comprehensive enough. Dashboard and report personalization take time and efforts, and sometimes it feels that a dedicated BI tool would be a more suitable solution.