In-memory computing is one of the advances that sets SAP Hana apart from all other business database software. For many business users, having access to a massive collection of data isn’t useful if there is no way to process that data to develop meaningful insights. The nature of business suggests that the data should be handled quickly since the face of marketing can change from hour to hour.
Data processing suits have traditionally been able to provide information to its users over some time. The pace of modern business development suggests that something to allow for real-time processing of massive amounts of data is not only necessary, but it’s also crucial to a business’ success in the long term. In-memory computing provides such a solution for companies utilizing the SAP Hana system.
Understanding the SAP In-Memory Computing Engine (IMCE)
The SAP IMCE is the core of the rapid processing that happens inside the SAP system. In-memory computing, combined with revolutionary technology such as massively parallel processing, data compression, and columnar databases, offer new ways for businesses to develop insight from their data. Having the entire database stored in memory makes for faster processing of data meaning that results can be generated on-the-fly, giving an accurate analysis of company data as it comes in.
Developing a System Architecture to Support SAP Hana
One of the best things about SAP Hana from a business perspective is its ability to scale with an enterprise’s growth. However, how a company decides to approach this scaling affects how the company invests in its system architecture. If the business decides it would prefer to scale up, then a single dedicated server built for power could handle the processing needs of the system. Alternatively, if a business decides to scale out, then multiple servers would be needed, but each server would be more affordable as they don’t all need to have extensive processing capability.
Sizing the SAP Hana System
Sizing affects both the performance and usability of the SAP Hana install. SAP has a handy sizing guide for companies looking at figuring out how much space they need to allocate for their particular installation. It is essential for a company to work out sizing details before developing its architecture since the sizing aspect of the database is crucial to its operation. Since SAP Hana uses an in-memory database, things like disk size, RAM and CPU are the main matters for a company to consider when sizing its SAP Hana install.
SAP Hana Architecture Overviews
There are multiple ways a company can decide to set up its SAP Hana installations, including:
- Dedicated System: These are designed to operate with a single Hana system, tenant database, dedicated server, and disk for storage. They are the most common installation in production environments.
- Partitioned Operation: In this case, a company dedicates a single drive to hosting multiple partitions with a different Hana install operating independently on each partition, each with its own operating system and file structure.
- Multi-Tenant Database System: This uses a system database which houses a series of smaller tenant databases. These types of installation work well in development environments, where having access to multiple test databases is a must.
- VMWare Virtualization: Several SAP Hana systems can be run in tandem on the same server using virtualization. Each system operates on its own virtual partition, without having to partition a hard drive, thanks to VMWare.
- Multiple Instances: Multiple installs can be done on the same or separate servers, allowing for multiple instances of different SAP databases to be operated at the same time.
- Multi-Component Combined System: These systems use separate Hana installs, but utilize the same hardware. A company can combine multiple instances of different installs into a single piece of equipment.
Depending on the needs of the business and what a particular Hana install is trying to accomplish, there are a lot of ways a company can design its system architecture around SAP Hana’s in-memory processing system.