By Aayushi Mittal | August 11, 2018
Neo4j with IoT makes sense to the Data Market.
This year is an expansive one for the database ecosystems that have evolved around the major platforms. Artificial intelligence, machine learning, the Internet of Things, and cloud computing are now mainstream offerings seen within the constellations of database vendors, partners, and integrators.This is a new day for relational database management systems, their vendors, and the huge ecosystem that has been built up over the years to support them. All the RDBMS players already extend themselves beyond traditional relational-model databases to support different unstructured data and columnar formats.
While still evolving, clients are increasingly exploring these options and moving away from deploying just a database. They are now thinking about how and where data can be stored and consumed as a service irrespective of the underlying database.
AI AND MACHINE LEARNING SHAPE THE MARKET
The trend that is generating the most buzz across database markets this year is the use of AI and machine learning—which is heavily data-dependent, and thus, directly impacting discussions and acquisition choices. "Most companies want to do something with AI and machine learning, but they have zero idea what that something is," said Robert Reeves, co-founder and CTO of Datical.
THE VALUE OF IOT
IoT is "another type of network within which we can create applications that blend what people do within that network," said Jeff Morris, head of product marketing at Neo4j. At the same time, "it’s not enough for businesses to just accumulate data—they also have to be able to act on it," Yu Xu, CEO of TigerGraph, pointed out."Today, most IoT users—businesses, governments—are collecting the data but have challenges making sense of it to drive value." Imagine a city that is better able to program traffic lights to improve traffic flow based on in-the-moment feedback after an accident. Saving 30 minutes in traffic is quite meaningful.”
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Keywords: AI / Machine Learning cloud Connected Data data model data modeling Graph Databases graph query language graph technology IoT meta models neo4j rdbms relational data model