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Description
A Kudu cluster comprises tables that resemble those found in traditional relational (SQL) databases. These tables can range from a straightforward binary key and value structure to intricate designs featuring hundreds of strongly-typed attributes. Similar to SQL tables, each Kudu table is defined by a primary key, which consists of one or more columns; this could be a single unique user identifier or a composite key such as a (host, metric, timestamp) combination tailored for time-series data from machines. The primary key allows for quick reading, updating, or deletion of rows. The straightforward data model of Kudu facilitates the migration of legacy applications as well as the development of new ones, eliminating concerns about encoding data into binary formats or navigating through cumbersome JSON databases. Additionally, tables in Kudu are self-describing, enabling the use of standard analysis tools like SQL engines or Spark. With user-friendly APIs, Kudu ensures that developers can easily integrate and manipulate their data. This approach not only streamlines data management but also enhances overall efficiency in data processing tasks.
Description
The RDC Platform enhances expert human expertise with advanced AI functionalities, equipping financial institutions with a distinct advantage in the lending sector. With an emphasis on ethical AI principles to maintain compliance, our tools enable lenders to visualize and comprehend the reasoning behind each AI-driven predictive model and decision-making strategy. By harnessing a combination of traditional, alternative, and latent data alongside cutting-edge AI methodologies, we facilitate precise predictions and optimal decision-making results. Recognizing the importance of safely integrating AI, we have developed a distinctive approach known as the Self-describing decision, which fosters confidence and transparency in achieving your safety objectives. This innovative concept encapsulates all components in a single data object, elucidating every aspect involved. It provides a thorough record of all model features, predictions, reference data, and rules activated during the decision-making process. With governance and explainability inherently incorporated, we ensure that these elements are consistently present, reinforcing the reliability of AI-driven decisions. This comprehensive strategy not only supports compliance but also builds trust in AI technologies within the financial sector.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Apache Flink
Yes
Apache NiFi
Yes
Apache Spark
Yes
BigBI
Yes
Cloudera Data Warehouse
Yes
E-MapReduce
Yes
Hadoop
Yes
nCino Cloud Banking Platform
No
Integrations
Apache Flink
No
Apache NiFi
No
Apache Spark
No
BigBI
No
Cloudera Data Warehouse
No
E-MapReduce
No
Hadoop
No
nCino Cloud Banking Platform
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
kudu.apache.org/overview.html
Vendor Details
Company Name
Rich Data Co
Founded
2016
Country
Australia
Website
www.richdataco.com
