Gartner predicts exponential growth of graph technology
As the size and complexity of data continues to escalate, organizations will increasingly turn to graph technology as a means of harnessing their data to drive decision-making.
During the keynote address on Oct. 5 of Graph + AI Summit Fall 2021, a hybrid in-person and virtual conference hosted by graph database vendor TigerGraph, Gartner analyst Rita Sallam said the research and advisory firm forecasts that 80% of data and analytics innovations will be made using graph technology by 2025.
Currently in 2021, just 10% of data and analytics innovations are made with graph technology.
At the core of graph technology are relationships between data points.
Data points stored in graph databases are able to connect with multiple other data points at any given time while those stored in traditional relational databases are able to connect with only one other data point at any time. That ability to connect to multiple other data points, meanwhile, enables deeper, faster and more accurate data exploration. In addition, as the amount of data being created and collected increases exponentially, traditional tools are getting overwhelmed and their performance is no longer meeting the needs of many organizations, according to Sallam. Graph technology, however, is able to handle the increasing demands of organizations. “As the size and the complexity and the distributed nature of data needed to contextualize complex decisions accelerates, rigid architectures and tools are breaking down,” Sallam said. “Agility and resilience are key, and the complexity is pushing the limits of current approaches, but [complexity] is also leading to unprecedented cycles of rapid innovation in data and analytics.” She added that the way to respond to the breakdown of rigid architectures and tools is to adopt graph technology — and maximize its effectiveness by combining it with augmented intelligence and the cloud. “We believe there will be rapid adoption,” Sallam said.
To illustrate the capabilities of graph technology, Sallam discussed several seemingly unrelated real-world examples of organizations using graph to solve problems. First, she spoke about the importance and unpredictability of supply chain management during the COVID-19 pandemic. The balance between supply and demand of certain products has been in constant flux over the past 18 months, and manufacturers have had to react quickly in order to avoid too much or too little of a given product in a given region at a given time. Next, Sallam noted that municipalities have had to deliver food to elderly citizens unable to leave their homes during the pandemic. Cities have had to determine the best routes to optimize delivery speed and transportation resources. Finally, she mentioned tracking the impact of climate change on penguins to determine intervention strategies. Environmentalists need to know the movement of individual penguins, migratory and mating patterns, and how it all relates to weather patterns and changes in their ecosystem.
