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Data Warehouse vs Database – A Comparison

The world of data is exploding for businesses and across industries. That said, it is no mean feat to convert this data into insights that can transform your business. To cut through the noise, it falls upon the organizations to implement best practices of enterprise data management using tools like SAP Analytics Cloud or Incorta Data Analytics Platform to create, store, manage, evaluate, and access the information 24×7.

Take the example of the onboarding employees using SAP HCM Successfactors solutions that bring the supporting systems, processes, and people together offering a more intuitive digital experience. The entire process of onboarding generates a tremendous volume of data from multiple source points which needs to be collated and stored in a secure space.

This is where a tool like an SAP data warehouse or a database enters the picture.

Not sure what the difference is between the two? Let’s do a short comparison to find out more.

What is a Database?

A collection of related information that represents select elements of the real world is commonly referred to as a database. This is a platform that is typically developed to absorb all the data for a specified task. A database is generally known as the building block of your enterprise data solution.

What is a Data Warehouse?

A data warehouse, on the other hand, is a system that captures and stores all the historical and commutative data that has been collected from single or multiple sources. The platform is designed to assess, report, and integrate all types of transaction data gathered from various sources.

What are the Key Differences Between a Database and a Data Warehouse?

Take a look at the key differentiators between a database and a data warehouse.

1. OLTP vs. OLAP

Online transaction processing or OLTP is a data processing term where the system focuses on transactions only. This is a common paradigm in databases where the information that the system contains is used to conduct daily business operations enabling employees to access data that is fast, efficient, up-to-date and accurate.

Online analytical processing or OLAP is frequently used in relevance to data analysis and decision-making unlike daily performance in a data processing system. The OLAP solutions work well with data warehouse systems enabling them to aggregate current data as well as historical information in a more efficient manner.

2. Number of Concurrent Users

As the majority of the databases come with OLTP systems that are able to support multiple users that can run into thousands at the same time. This in no way degrades the performance of the system.

Data warehouses with OLAP are only able to support a limited number of concurrent users at any given point in time. This is primarily due to the fact that the system utilizes more complex queries reaching out for multiple data stores at the same time.

3. Use Cases

The use case of a database and a data warehouse is vastly different.

The database is best suited to process transactional data that is small in size and is mostly required for running day to day operations and functions of the business.

The data warehouse, for instance, the SAP data warehouse is better equipped to answer more complex questions that can involve the past, present and future of the organization through a greater degree of analysis and assessment. Eventually, the evaluation generates a series of useful insights that can accelerate better decision making for the business.

In Conclusion

Whether your business needs a database, or a data warehouse will largely depend on the needs of the organization. However, if you to better understand your requirements, it is best that you consult with an expert.

MDSap has been in the business of data solutions including SAP data warehouse for several years. Speak to an MDSap expert today.

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