TOP LEADING TECHNOLOGIES FOR CUTTING-EDGE DATA PROCESSING SYSTEMS
Data processing technologies are developing as rapidly as data collection is advancing, that is, at a continually accelerating rate. There’s a whole lot of technology that is breaking ground and offering new solutions in this exciting field.
Let’s take a look at what some of the latest cutting-edge technologies are for data processing systems.
DISTRIBUTED SYSTEMS ARCHITECTURE
Big data sets common in data processing today have limitations on computational power. The technology needed to deal with this is called distributed systems architecture.
MPP – Massive parallel processing, and Hadoop are two key technologies that are leading the industry in distributed systems architecture. Both feature the “shared nothing” technology that ensures autonomous operation.
The key difference between the two is that MPP is proprietary and rather costly to implement, while Hadoop is open source and can be integrated from very small, low cost applications, to very very large ones. While Hadoop is more recent than MPP, and allows flexibility and scalability, MPP remains slightly quicker.
MPP systems are provided by Teradata, Netezza, Vertica, and Greenplum. Oracle and Microsoft also have their own MPP systems.
Hadoop is a software project by Apache, containing a collection of software utilities that provide huge storage and processing power. Hadoop uses MapReduce to process large non-structured data sets, as the name implies, by a map function, and a reduce function within Hadoop. Many platforms can be built on top of the Hadoop framework. Non-proprietary applications available for use on Hadoop continue to develop in number and complexity.