# GreenplumAWSStreamingData

**Repository Path**: mirrors_greenplum-db/GreenplumAWSStreamingData

## Basic Information

- **Project Name**: GreenplumAWSStreamingData
- **Description**: Demonstratea Close loop analytics scenario with  Greenplum, AWS Kinesis, SQS, Lambda, S3, PXF, RTSMadlib.
- **Primary Language**: Unknown
- **License**: BSD-2-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-12-16
- **Last Updated**: 2025-09-28

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

**VMware has ended active development of this project, this repository will no longer be updated**

# GreenplumAWSStreamingData

This Git project goal is to demonstrate Closed loop analytics with Greenplum leveraging AWS cloud native tools.

The Demo application choosed it a credit card fraud transaction Machine learning model. The Model will be built and tested on Greenplum using sample application in samples section of [RTSMADlib](https://www.google.com/url?q=https://github.com/pivotal/Realtime-scoring-for-MADlib&sa=D&source=hangouts&ust=1584626576096000&usg=AFQjCNEppB_6B4bN6Tg-eUv1O1qOuvKAkg). The model is then deployed on Amazon EKS to integrate in to streaming solution via Amazon Java Lambda. 

The streaming part is built with all AWS cloud native tooling;
* AWS Kinesis Stream
* AWS Kinesis S3 Firehose
* Pivotal Greenplum PXF, 
* AWS SQS 
* AWS Lambda
* RTSMadlib to deploy ML models on AWS EKS.

## The Document embeds a [demo](https://onevmw-my.sharepoint.com/:b:/g/personal/spaladugu_vmware_com/Efl7dpRv5-xEm3yAqi0g6EUBcZdhd3py5wVpYrehJB332Q?e=QsSOzu)

The overall folow can be shown as ;
![](/VmwareGreenplumStreamingMLUsecaseOnAmazonAWS.svg)