In-Memory First
SAP achieved a true transaction and analytical (i.e. translytical) platform by designing SAP HANA from the ground up with a new data processing architecture in mind. This architecture greatly simplifies applications built on this platform removing many of the legacy overhead required to optimize applications on traditional disk-based database solutions.
SAP HANA is the only true in-memory columnar data store optimized for both high-speed transactional scenarios and also very fast query performance optimally supporting both OLTP and OLAP application scenarios. With SAP HANA, there is a single copy of data as there is no need to move data to external systems to offload analytic workloads or populate materialized views and in-memory caches to achieve acceptable performance. This allows applications built on SAP HANA to process transactional and analytical workloads at high speed without any data duplication enabling businesses to have accurate insights based on the latest data.
Other solutions in the market typically provide an in-memory “option” to existing disk-based, row-oriented solutions, requiring a copy of data to be made into in-memory storage. Row-based storages don’t yield the same level of data compression as columnar storages leading to higher costs and inefficiencies. These solutions may provide some performance improvements in certain use-cases, but they do not deliver the overall value that SAP HANA does by truly reducing the data footprint, increasing overall performance for all data and reducing management costs of the solution.
Scalability and Speed
Based on the functionality of data being stored in a RAM chip instead of a hard disk, SAP HANA makes high speed processing a practical reality. Unlike the traditional process of data being read from the hard-disk and subsequently moved into RAM for data processing, the agility of SAP HANA allows organizations to achieve more with their data. For instance, an HR team could run real-time jobs in different batches without having to wait for the jobs to get completed before starting another. The fantastic capability of running multiple jobs at the same time and run them several times, if need be, gives SAP HANA an edge above the rest.
Simplicity
The biggest problem of traditional databases was their limitation of supporting and managing one business load at a given point in time. So, if a customer runs multiple businesses or has more than one line of operations such as marketing, customer support, logistics, manufacturing, finance, and more; the data in each of these systems will tend to get duplicated thus, increasing the complexity of the system manifolds. The process gets further complicated if the customer wants to view multiple kinds of data at one time. With SAP HANA integration, the simplicity of having one system for different business applications and its real-time access makes the operations extremely simple and user-friendly.
Predictive analytics and machine learning
Predictive analysis with SAP HANA includes native high-performance predictive algorithms for both expert and automated modes. Additionally, you can run open-source R scripts on SAP HANA through integration with R server and build machine learning applications with integration to TensorFlow. Some of the predictive algorithms run on streaming, spatial, and series data and are self-improving. The ability to perform predictive analytics on an entire body of transactional data lets you develop modern applications that forecast outcomes and help your business adapt processes in real time. Machine learning helps you build applications that can adapt and automate some of the manual business process step.
Read the full blog post on www.approyo.com
No comments:
Post a Comment