Graph Database Market Growth
Graph Database Market Growth
Graph database offerings and implementations are growing at a rapid rate
Fluree and Zettalabs announced a recent merger that will combine a graphing database venture with an AI/Machine Learning platform. The market for these types of solutions is expected to triple from the current value mark of about $1 billion to over $3 billion by 2024 given the increased demand in recent years. Voluminous amounts of dispersed, highly unstructured data are being accumulated by organizations at an ever-increasing velocity and the need for a system that can incorporate all potential relationships and amalgams of a particular information grouping is essential.
Recent improvements in associated technologies have enhanced the speed and flexibility of graph databases to the point where the primary difficulties once seen with its usage are no longer potential barriers to implementation. There have also been some difficulties regarding having a uniform query language in place, but that is rapidly being addressed by the primary operators in the field in the form of GraphQL which should be in place and viable during the latter part of 2023. Given this increased shift by many from a purely relational database approach it’s clear that the inherent advantages will continue to propel much greater acceptance across numerous verticals.
A number of fields are realizing strong value
• Healthcare – The massive population cohorts involved require effective methods of establishing various correlations that are more readily computed via a graph database.
• Financial Services – Account safety, fraud prevention, compliance, staving off money laundering activities, and a host of additional initiatives and needs are all made much easier with a fully scaled graph distribution.
• Supply Chain and Logistics – Strong value is being found in this vertical by implementing a graph solution with an ERP system already in place in order to fully maximize observations and insights in real time.
• AI and Machine Learning – Everything from phone call source characteristics to group ecommerce targeting can be readily improved and analyzed with far greater efficiency.
• Digital Asset Management and Monitoring – Another corporate requirement seemingly made for this type of approach.
• Grid Management – Telecommunications, power services, and various public sector infrastructural systems are finding a graphic representation solution to be highly effective at amassing and providing a cohesive view of often countless sources of information.
• Identity Access Management Systems – Certainly a very strong potential usage area given the inherent strengths of graph databases being utilized in an environment that requires rapid relationship processing and clarification.
• Social Media – Many companies in this vertical find this approach to data management to be indispensable given the disparate information amassed by their systems and users.
Continued adoption and implementation
Graph database appropriation by a diverse set of companies and technology groups has been pronounced in recent years. We’ve completed a number of searches for ventures operating in the realm and anticipate that a host of additional industries and technology leaders will continue to add this tool to their operational capacities as conventional databases reach their operational limits. Undoubtedly relational offerings and other parallel systems will remain in place and remain quite useful for many corporate needs. The key factor to be seen is how well will each be able to be employed within various ecosystems and to what degree will one or the other supplant a particular approach as an overall or perhaps hybrid solution.
