The Text Analytics component extracts information from unstructured and semi-structured data. By using its components, enterprises can analyze large volumes of text and produce annotated documents that provide valuable insights into unconventionally stored data.

The Text Analytics component only extracts information from structured data stored in a relational database.

The Text Analytics component is a programming model for processing large data sets, and the name of an implementation of the model by Google. Text Analytics is typically used to do distributed computing on clusters of computers.

Jaql is the language for developing text analytics extractors in the InfoSphere BigInsights Text Analytics system. A Jaql extractor is a program written in Jaql that extracts structured information from unstructured or semi-structured text.

A Hadoop feature capable of processing vast amounts of data in-parallel on large clusters of commodity hardware in a reliable, fault-tolerant manner.

A concept and platform of technologies with the characteristics of the ? Vs? that is able to handle large amounts of unstructured,semi-structured, and structured raw data unlike traditional systems.

A database feature capable of converting pre-existing structured data into unstructured raw data.

Only data stored in the BIGDATA table in any relational database.

It cuts costs by providing an efficient compression algorithm based on row level compression using a dictionary to store repetitive patterns.

It complements your existing infrastructure by extending your data collection and analysis capabilities.

It integrates data from a variety of structured and unstructured sources.

It enables analysis at scale.

Big data solutions must substitute the existing enterprise infrastructure; therefore there is no interaction between them.

Big data solutions are only plug-ins and additions to existing data warehouses, and therefore cannot work with any other enterprise infrastructure.

Big data solutions must be isolated into a separate virtualized environment optimized for sequential workloads, so that it does not interact with existing infrastructure.

Big data solutions works in parallel and together with the existing enterprise infrastructure, where pre-existing connectors are used to integrate big data technologies together with other enterprise solutions.