Top 10 SAP and Open Source Technology based projects that can be implemented in real business scenario

by Barry Allen | May 11, 2023 | Projects, SAP

Table of Contents

Introduction

As SAP continues to evolve, it’s no surprise that it’s working with open source technologies to provide even more value to its customers. In this article, we’ll explore the top 10 SAP and Open Source Technology based projects that can be implemented in real business scenarios. From leveraging open source databases to integrating with popular open source frameworks, these projects showcase the power of combining SAP’s expertise with the innovation of the open source community. We’ll delve into each project’s details to provide a comprehensive understanding of how they can benefit businesses in various industries.

Top 10 SAP and Open Source Technology based projects

Here is a detailed explanation of each of the top 10 SAP and Open Source Technology-based projects that can be implemented in real business scenarios:

1. Integration of SAP and Apache Hadoop:

This project involves integrating SAP systems with Apache Hadoop, an open-source framework that allows distributed storage and processing of large data sets across clusters of computers. This integration enables businesses to handle and analyze vast amounts of data using SAP tools and applications.

2. SAP BusinessObjects and Pentaho BI integration:

This project involves integrating SAP BusinessObjects, a business intelligence platform, with Pentaho BI, an open-source BI suite. This integration helps organizations to get a comprehensive view of their data, make informed decisions, and improve overall business performance.

3. SAP and MongoDB integration:

This project involves integrating SAP systems with MongoDB, an open-source NoSQL database that offers flexibility, scalability, and high-performance data storage. This integration enables businesses to store and analyze large volumes of data generated by SAP systems using MongoDB.

4. Integration of SAP and Apache Kafka:

This project involves integrating SAP systems with Apache Kafka, an open-source streaming platform that enables real-time data processing. This integration helps businesses to stream and process data from SAP systems in real-time and take immediate action.

5. SAP and PostgreSQL integration:

This project involves integrating SAP systems with PostgreSQL, an open-source relational database management system. This integration enables businesses to store and manage data using SAP systems and PostgreSQL.

6. SAP and Apache Spark integration:

This project involves integrating SAP systems with Apache Spark, an open-source big data processing framework. This integration enables businesses to process large amounts of data using SAP tools and applications and perform real-time analysis.

7. Integration of SAP and ElasticSearch:

This project involves integrating SAP systems with ElasticSearch, an open-source search and analytics engine. This integration enables businesses to search, analyze, and visualize data generated by SAP systems using ElasticSearch.

8. SAP and Apache Cassandra integration:

This project involves integrating SAP systems with Apache Cassandra, an open-source distributed database management system. This integration enables businesses to store and manage large volumes of data using SAP systems and Apache Cassandra.

9. Integration of SAP and Docker:

This project involves integrating SAP systems with Docker, an open-source platform for building, shipping, and running applications in containers. This integration enables businesses to deploy SAP applications quickly and efficiently in a containerized environment.

10. SAP and Kubernetes integration:

This project involves integrating SAP systems with Kubernetes, an open-source container orchestration platform. This integration enables businesses to manage and deploy SAP applications in a scalable and reliable manner using Kubernetes.

Overall, integrating SAP systems with open-source technologies can bring significant benefits to businesses, including improved data management, real-time data processing, and cost-effectiveness.