Challenge 1: Massive Data Growth
Massive amounts of data is being created every year and as per he IDC EMC report data growth would be 40K Exabytes by 2020 :
Challenge 2: Fast access to business decision making information.
Business & People want fast exact and correct answer of all questions from this massive amount of data.
Challenge 3: Current Technologies Can not deliver with this massive data growth.
Historical DBMS :
Historically database systems were designed to perform well on computer systems with limited RAM, this had the effect that slow disk I/O was the main bottleneck in data throughput. Consequently the architecture of these systems was designed with a focus on optimizing disk access, e. g. by minimizing the number of disk blocks (or pages) to be read into main memory when processing a query.
New Hardware Architecture ( up to or more 128 Cores of CPU and 2TB of RAM)
Computer architecture has changed in recent years. Now multi-core CPUs (multiple CPUs on one chip or in one package) are standard, with fast communication between processor cores enabling parallel processing. Main memory is no-longer a limited resource, modern servers can have 1 TB of system memory and this allows complete databases to be held in RAM. Currently server processors have up to 80 cores, and 128 cores will soon be available. With the increasing number of cores, CPUs are able to process increased data per time interval. This shifts the performance bottleneck from disk I/O to the data transfer between CPU cache and main memory
Need of In-memory Technology SAP HANA :
From the discussion above it is clear that traditional databases might not use current hardware most efficiently and not able to fulfill current and future business need.
The SAP HANA database is a relational database that has been optimized to leverage state of the art hardware. It provides all of the SQL features of a standard relational database along with a feature rich set of analytical capabilities.
Using groundbreaking in-memory hardware and software, HANA can manage data at massive scale, analyze it at amazing speed, and give the business not only instant access to real time transactional information and analysis but also more flexibility. Flexibility to analyze new types of data in different ways, without creating custom data warehouses and data marts. Even the flexibility to build new applications which were not possible before.
HANA Database Features
Important database features of HANA include OLTP & OLAP capabilities, Extreme Performance, In-Memory , Massively Parallel Processing, Hybrid Database, Column Store, Row Store, Complex Event Processing, Calculation Engine, Compression, Virtual Views, Partitioning and No aggregates. HANA In-Memory Architecture includes the In-Memory Computing Engine and In-Memory Computing Studio for modeling and administration. All the properties need a detailed explanation followed by the SAP HANA Architecture.
Source : www,sap.com and emc and idc reports.