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SAP HANA Database
Traditional database management systems are designed for optimizing performance on hardware with constrained main memory. Disk I/O was the main bottleneck. The focus was on optimizing disk access, for example, by minimizing the number of disk pages to be read into main memory during processing.
The SAP HANA database is designed from the ground up around the idea that memory is available in abundance, considering that roughly 18 billion gigabytes or 18 exabytes are the theoretical limits of memory capacity for 64-bit systems, and that I/O access to the hard disk is not a constraint. Instead of optimizing I/O hard disk access, SAP HANA optimizes memory access between the CPU cache and main memory.
SAP HANA
is a massively parallel (distributed) data management system that runs fully in main memory, allowing for row- and columnbased storage options, and supporting built-in multitenancy.
SAP HANA serves as a foundation to develop future in-memory analytic and transactional applications.
The SAP HANA database can potentially provide performance improvements for existing SAP applications where, for example, SAP applications that use Open SQL can run on SAP HANA without changes.
New applications developed natively on SAP HANA and powered by SAP HANA can improve performance of business process and analytical scenarios. Application development techniques optimized for parallel in-memory processing can take advantage of new enterprise data management and application development logic to fully exploit advances in hardware technologies.
The table summarizes the benefits offered by specific features of the SAP HANA database.
The SAP HANA database manages data in a multicore architecture for data distribution across all cores to maximize RAM locality using scale-out (horizontally) and scale-up (vertically) functionality.
In the scale-out scenario, the SAP HANA database scales beyond a single server by allowing multiple servers in one cluster.
Large tables can be distributed across multiple servers using round-robin, hash, or range partitioning, either alone or in combination. SAP HANA has the functionality to execute queries and maintain distributed transaction safety across multiple
servers.
Specific server configurations for SAP HANA deployments are the responsibility of certified SAP technology partners. These partners can balance better performance per CPU at lower
cost, enabling customers to take advantage of larger memoryaddress spaces, lower data-center operating costs, and simpler management.
One of the major contentions and the reason for slow performance in traditional DBMS is locking data when data updates are being performed.
SAP HANA avoids this issue and enables high levels of parallelization using insert-only data records. Instead of creating new records in a database table, deltas are inserted as net-new entries in existing records stored in columns.
Using columnar data stores, SAP HANA can achieve major compression rates unheard of in traditional databases.
On one example, the analysis of SAP customers’ systems showed that
only 10% of attributes in a single financial database table was used in an SQL statement, shrinking the actual size of data volume to be accessed from 35 GB in traditional relational database management system (RDBMS) storage to 800 MB in a column-store design, just over 2% of the volume in the traditional storage. As this example shows, much higher compression rates will be accomplished with high-sparsity data than with dense data.