The Global Graph Database Market is forecast to reach USD 7.39 Billion by 2027. The growing importance of understanding & managing the big data and fostering enterprise-wide data to turn it into a meaningful insight so that actionable steps can be taken on time to sustain a competitive landscape. Object oriented visualization, real-time big data update with simultaneous supporting queries, powerful recursive network of data, advanced problem solving capabilities, and exhibiting constant performance in real-time of the data size growth are some of the key factors that have been increased the usability of the graph databases amongst the end-use verticals.

Operation management in IT and networking companies, instant recommendation engines, risk investigation & fraud detection, identity management, master data management, catalog management, access management, data relationship management and others have some of the most relevant use-cases of graph database. Starting from the global conglomerates to up till the start-ups and even the non-profit organizations are consistently making use of the graph databases to find unprecedented insights to carry out target marketing and set a persistent competitions and also use of numerous case studies to predict the best possible outcome.

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Further key findings from the report suggest

  • In November 2019, Neo4j, Inc., launched Aura, a fully managed cloud database that will run on Google cloud platform. The new development with Google cloud and developer-first approach by the company make Aura a highly demanded position in the market.
  • In June 2019, data.world, Inc., a US based company Graph Database & data analysis company announced its acquisition of Capsenta, Inc., a data virtualization company in order to enable businesses to securely able to access, view, relate and work with on-premises databases in the cloud.
  • Many data experts have estimated that nearly 70 percent of the data generated from the customers’ end remains unknown and unserviceable. Analytical insights would have been quite faster if only the relations and nodes of the data could be studied in real-time. That is where the graph database helps many business verticals providing with a super simplified analytical relationship to the vast big data and help derive faster and accurate insights.

Top 10 Companies Operating in the Global Graph Database Market: 

IBM, TIBCO Software Inc., Oracle Corporation, Amazon Web Services, Microsoft Corporation, Neo4j, OrientDB, OpenLink Software, DataStax, Inc., and TigerGraph, among others.

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The global market is further segmented into type and application:

Application Outlook (Revenue, USD Million; 2019-2027)

  • Consumer Analytics
  • Deep Learning
  • Regulatory Compliance
  • Recommendation Engines
  • Identity & Access Management
  • Fraud Detection
  • Supply Chain Management
  • Others

Deployment Mode Outlook (Revenue, USD Million; 2019-2027)

  • Cloud
  • On-premises

Type Outlook (Revenue, USD Million; 2019-2027)

  • Resource Description Framework
  • Property Graph

Organization Size Outlook (Revenue, USD Million; 2019-2027)

  • Large Enterprises
  • SMEs

End-Use Verticals Outlook (Revenue, USD Million; 2019-2027)

  • BFSI
  • Retail & E-Commerce
  • IT & Telecommunication
  • Transportation & Logistics
  • Others

Regional analysis provides insights into key trends and demands in each major country that can affect market growth in the region.

  • North America (U.S., Canada, Mexico)
  • Europe (Germany, U.K., Italy, France, BENELUX, Rest of Europe)
  • Asia Pacific (China, India, Japan, South Korea, Rest of APAC)
  • Latin America (Brazil, Rest of LATAM)
  • Middle East & Africa (Saudi Arabia, U.A.E., South Africa, Rest of MEA)

Key Takeaways of the Competitive Overview Section:

  • Overview of the company profiles of each market player
  • Industrial chain analysis of each player
  • Revenue share contribution
  • Sales network and distribution channels and net profits and losses of each company
  • Key business growth strategies are undertaken by these players

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