Global graph database market is expected register a 24.2% CAGR in the forecast period of 2019-2026

Global Graph Database Market By Type (Resource Description Framework, Property Graph ), Component (Tools and Services),  Application (Recommendation Engines, Fraud Detection, Customer Analytics, Risk and Compliance Management, Deployment Mode (On-Premises, Cloud), Organization Size (Small and Medium-sized Enterprises,  Large Enterprises), Industry Vertical (Retail and Ecommerce, Transportation and Logistics,  Healthcare and Life Sciences , Manufacturing, Government and Public Sector, Banking, Financial Services, and Insurance , Telecom and IT, Others), Geography (North America, Europe, Asia-Pacific, South America, Middle East and Africa) – Industry Trends and Forecast to 2026

Global graph database market is expected register a 24.2% CAGR in the forecast period of 2019-2026. Growing adoption and need in identifying the complex patterns along with the rapid use of virtualization for Big Data analytics are expected grow global graph database market

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Competitive Analysis

Global graph database market is highly fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market. The report includes market shares of graph database market for Global, Europe, North America, Asia-Pacific, South America and Middle East & Africa.

Major Market Competitors

Few of the major competitors currently working in global  graph database market are Oracle, IBM, Microsoft, Amazon Web Services, Inc., Neo4j, Inc., TIBCO Software Inc., Franz Inc, OpenLink Software,  TigerGraph, MarkLogic Corporation, Cray Inc, DataStax, Inc, Stardog Union, Ontotext, Bitnine Co, Ltd., Cambridge Semantics, ArangoDB, Kompass (UK) Ltd, Sparsity Technologies, Objectivity Inc., Teradata, MongoDB, Inc., among others.

Market Definition: Global Graph Database Market

Graph database is an online database management system. It is a part of NoSQL databases which is mainly created to address the limitations of existing relational databases. It consists of nodes and edges. It utilizes the graph theory for storing, mapping  and querying relationship. These database are widely used for solving critical business solutions such as supply chain management problem, customer relationship among others.

Market Drivers:

  • Growing   real-time big data mining with effect of visualization is expected to drive the growth of the market
  • Growing  demand of system  that  has capability to process low-latency queries is expected to drive the growth of the market
  • Increasing demand of AI-based graph database tools and services is also expected to boost the growth of the market
  • Technological advancements in the graph databases software and prevailing demand from the healthcare industry for enhanced accuracy is another factor uplifting the market growth

Market Restraints:

  • Lack of awareness among  consumers is expected to restrict the growth of the market
  • Dearth of standardization and programming ease is another factor which hamper the market growth
  • Scarcity of technical experts along with high initial expenditure also acts as  market restraint

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Segmentation: Global Graph Database Market

By Type

  • Resource Description Framework
  • Property Graph

By Application

  • Recommendation Engines
  • Fraud Detection
  • Customer Analytics
  • Risk and Compliance Management

By Organization Size

  • Small and Medium-Sized Enterprises
  • Large Enterprises

By Industry Vertical

  • Banking, Financial Services, and Insurance
  •  Retail and e-commerce
  • Transportation and Logistics
  • Government and Public Sector
  • Manufacturing
  • Telecom and IT
  • Healthcare and Life Sciences
  • Others

By Deployment Mode

  •  Cloud
  • On-Premises

By Component

  • Tools
  • Services

Key Developments in the Market:

  • In October 2019, TigerGraph had launched graph database named as TigerGraph cloud aservices which will further help the users to configure and manage their own database. It features pattern matching and data processing functions along with SQL like querying in making predictions and performing real time transactions. This will in turn help the business to minimize the administrative cost and enhancing the user’s performance
  • In April 2019, Neo4j and Google had entered in to strategic partnership. The purpose of this partnership is to integrate Neo4j graph database with google cloud further delivering the cloud-based graph database leveraging the connected data for maximum impact. This will further create innovation by providing best possible outcomes to its respective customers

Key Insights in the report:

  • Complete and distinct analysis of the market drivers and restraints
  • Key market players involved in this industry
  • Detailed analysis of the market segmentation
  • Competitive analysis of the key players involved


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