Evolution from Traditional Databases to SAP HANA In-Memory Computing

This tutorial covers the evolution from traditional databases to SAP HANA in-memory computing.

Understanding CDS requires understanding SAP HANA.

While CDS provides the data modeling layer, SAP HANA provides the processing engine that makes Code Pushdown possible.

Before SAP HANA, most enterprise databases stored data primarily on physical disks. Whenever an application requested information, the database had to read data from disk, load it into memory, process the request, and then return the result.

Although this architecture served enterprise systems for decades, disk access gradually became one of the largest performance bottlenecks as data volumes increased.

As organizations generated more transactional and analytical data, traditional databases struggled to provide real-time processing and reporting capabilities.

SAP needed a new database architecture capable of processing large volumes of data in real time.

This led to the introduction of SAP HANA.

SAP HANA stands for:

High-Performance Analytic Appliance

It is an in-memory relational database designed to process transactional and analytical workloads on a single platform.

Unlike traditional databases that rely heavily on disk-based storage, SAP HANA stores active business data directly in main memory (RAM).

Because memory access is dramatically faster than disk access, data can be processed much more efficiently.

This allows applications to perform complex calculations, aggregations, searches, and analytics in real time.

In a traditional system, data processing follows a multi-step path:

1. Data is stored on disk.
2. Required data is loaded into memory.
3. The CPU processes the request.
4. Results are returned to the application.

Every database request involves disk access, which introduces latency.

As datasets grow larger, these delays become increasingly noticeable.

This is one of the main reasons why older reporting applications often require batch jobs, aggregates, indexes, or pre-calculated totals.

SAP HANA fundamentally changes this architecture.

Instead of repeatedly reading data from disk, active business data resides directly in memory.

The processing flow becomes:

1. Data is stored in memory.
2. The CPU processes the request directly.
3. Results are returned immediately.

Because expensive disk reads are minimized, applications can execute complex calculations significantly faster.

This is the foundation that enables modern SAP applications to provide near real-time reporting and analytics.

The true power of CDS comes from its integration with SAP HANA.

CDS allows developers to define calculations, associations, aggregations, filters, and business logic at the data model level.

SAP HANA then executes those operations directly within the database.

Instead of transferring millions of records to the application server for processing, only the final result set is returned.

This dramatically reduces:

• Data transfer volume
• Network overhead
• Application server workload
• Memory consumption

while simultaneously improving performance and scalability.

The introduction of SAP HANA was not merely a database upgrade.

It fundamentally changed how SAP applications are designed and developed.

Technologies such as:

• CDS
• RAP
• Embedded Analytics
• Fiori Elements
• OData Services

all rely heavily on SAP HANA's in-memory architecture and processing capabilities.

Without SAP HANA, concepts such as Code Pushdown and modern CDS-based application development would not be possible.