Big Data and the Multi-model Database

Gartner showing in their report, Top 10 Strategic Technology Trends for 2017, interesting things like Artificial Intelligence and Advanced Machine Learning, Intelligent Apps, Intelligent Things and Conversational Systems. All this added to the buzz on Big Data, the business people realize that data, in all forms and sizes, is critical for making the best possible decisions to win the competition over customers. According to Gartner (Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics 2016), “Organizations now require data management solutions for analytics that are capable of managing and processing internal and external data of diverse types in diverse formats, in combination with data from traditional internal sources. Data may even include interaction and observational data — from Internet of Things sensors, for example. This requirement is placing new demands on software in this market as customers are looking for features and functions that represent a significant augmentation of existing enterprise data warehouse strategies.” These needs give a lot of pressure for the technology. One of the problems recognized is the different data models for different types of data but even more problematic is finding a single query language to query all the different data. Usually the user needs several query languages to query from different sources and then a query language to somehow join the data together to get sense of it. One of the solutions is multi-model database. That is a database that stores several data models in one single database allowing the user to query the data using one single query language and joining all data of different data models together. What is this multi-model database and how close is Oracle database to be one? This session talks about the different data models and how well Oracle Database supports them.