IBM Integrated Analytics System

2017: Announcement

In October, 2017 the IBM corporation provided a high-performance analysis system of data. By means of the new solution which received  the name Integrated Analytics System and using mechanisms of artificial intelligence, the companies will be able quicker to process data bulks (Big Data) and it is essential to save the time.

 Integrated Analytics System uses the IBM Common SQL Engine engine providing moving of working tasks to a public cloud. The solution also involves such components as IBM Data Science Experience, Apache Spark and Db2 Warehouse which are optimized for joint work.

IBM Integrated Analytics System

Within Data Science Experience tools for processing of crucial data and a joint working space using which specialists can create new analytical models are offered, and developers — to apply these models to creating applications.

Framework open source Apache Spark allows to process data in RAM, accelerating work of analytical applications.

Besides, IBM equipped  Integrated Analytics System with opportunities of machine learning at the expense of which data do not need to be moved for carrying out the analysis that reduces number of necessary actions and a downtime because of waiting of start and a response of an analytical system. Such approach simplifies learning process and estimates of forecast models and also their testings and deployments as everything occurs in a single system, says the producer.

This system supports work with data in private, public or hybrid cloud environments. The integrated architecture includes asymmetric mass parallel processing of data (AMPP), IBM Power technologies and hardware of storage on a basis a flash memory.^[1]

The integrated architecture of a new system combines functions of the software, such as asymmetric mass parallel processing of data (AMPP), with IBM Power technology and hardware of storage on a basis a flash memory. A system is constructed based on IBM PureData System for Analytics and the previous solutions in the field of IBM Netezza data warehouses. Besides, it supports a broad set of types and services of data, beginning from IBM Watson Data Platform and IBM DB2 Warehouse On Cloud to Hadoop and IBM BigSQL. Like these solutions, Integrated Analytics System it is constructed based on IBM Common SQL Engine that allows customers to integrate a local system and cloud storages with ease.

Besides, standard industry tools and the standard SQL mechanism allow to move easily workloads to public or private clouds using Spark clusters taking into account user requirements.

As well as all existing data warehouses of IBM, Integrated Analytics System offers the built-in virtualization of data and compatibility with Netezza, Db2 and IBM PureData System for Analytics.

In addition to the listed opportunities, a new system also offers hybrid transactional and analytical processing (HTAP). Unlike normal business environments where such processes are started based on separate architecture, HTAP manages predictive analytics, transaction and archive information in the single database with the accelerated answer time. Later this year the company is going to add support of HTAP on IBM Db2 Analytics Accelerator for z/OS that will simplify integration of a system with infrastructure of IBM z Systems.

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