Companies mine data warehouses for a wide variety of purposes, including business intelligence and analytics. Many organizations are depending on data infrastructures to create a competitive advantage. This has led to a demand for quicker and more robust ways to access and transfer data from legacy systems, such as transactional processing databases, among others. Data replication programs play a critical role in keeping the databases up to date. Companies prefer replication solutions that have the capacity to handle bulk data loading easily and efficiently. The changes are applied to the Greenplum database, which reads the source schema before creating destination database tables automatically.

Data replicators typically take advantage of Greenplum’s parallel loading capabilities to replicate data into its resources. The Change Data Capture (CDC) is automatically configured once the process is complete. The data is yielded from an extensive array of sources, including automated data collection sensors, online purchases, electric meter readings, RFID data, cell phone data, social media sites, business transactions and much more. The amount of big data being processed is forever increasing in the order of Terabytes, Exabytes and Zettabytes. The big data provides companies with a viable way to identify trends more accurately. In the end, organizations use the insights gained from data replication Greenplum to make better operational decisions that enhance competitiveness in a fast-paced business environment.

Greenplum’s design is based on a share-nothing Massively Parallel Processing (MPP) architecture, which is aimed at enabling analytical processing and business intelligence. To achieve the no disk-level sharing, data is synchronized across a number of segment servers in the Greenplum database. Segment servers have the capacity to handle queries in a parallel fashion to promote scalability. Some of the major benefits of the Greenplum database include the ability to continuously balance resources across queries in real-time. In addition, the database is capable of dynamic query prioritization, quick online differential recovery, providing intelligent fault detection and polymorphic data storage.

The technology incorporates support and compression for column oriented and row storage. Greenplum Data Computing Appliance (DCA) is a massively parallel processing data warehousing system that is a purpose-build. It is designed to integrate networking and storage into a single enterprise-class system. It comes with considerable scalability benefits to accommodate the ever-increasing storage needs of business organizations. It uses storage and network switches as well as commodity servers to reduce operating costs. The program employs a share-nothing architecture capable of loading huge amounts of data and queries much faster while maintaining the highest degree of parallelism. The EMC Data integration Accelerator (DIA) leverages numerous data integration applications, including Attunity Replicate and Informatica PowerCenter. The accelerator is purpose-built for micro-batch loading and batch loading.