Graph Database Market by Component (Software and Services), Deployment Model (On-premise and Cloud), Type of Database (Relational (SQL) and Non-relational (NoSQL)), Analysis Type (Path Analysis, Connectivity Analysis, Community Analysis and Centrality Analysis), Application (Fraud Detection & Risk Management, Master Data Management, Customer Analytics, Identity & Access Management, Recommendation Engine, Privacy & Risk Compliance, and Others), Organization Size (Large Enterprises and Small & Medium Enterprises), Industry Vertical (BFSI, Retail & Ecommerce, IT & Telecom, Healthcare & Life science, Government & Public Sector, Media & Entertainment, Manufacturing, Transportation & Logistics, and Others): Global Opportunity Analysis and Industry Forecast, 2019–2026
A graph database is an online database management system where connected elements are linked together. It is an ideal solution to store data and to connect relationships between the data much more accurately than a relational database (RDBMS). A graph database is gathering of nodes and edges where every node represents a substance, for example, a person or business and each edge represents a connection or relationship between the two nodes. Each node in a graph database is characterized by a unique identifier, an arrangement of active edges as well as incoming edges and a set of properties communicated as key/value sets. In addition, each edge is characterized by a unique identifier, a beginning spot as well as ending-place node, and a set of properties.
Factors such as surge in adoption for graph database software in the healthcare sector, increase in application areas of graph database, increase in need for better response time & accuracy to discover new data correlations, and upsurge in penetration of connected data to optimize marketing performance fuel the growth of the graph database market. However, lack of technical expertise and high setup costs hinder the growth of graph database market. On the contrary, increase in use of virtualization for big data analytics and technological advancements in graph database technology are expected to provide lucrative opportunities for the market.
The global graph database market is segmented into component, deployment model, type of databases, analysis type, application, organization size, industry vertical, and region. Based on component, the market is bifurcated into software and services. Based on deployment mode, the market is divided into on-premise and cloud. Depending on analysis type, it is classified into path analysis, connectivity analysis, community analysis, and centrality analysis. Application segment includes fraud detection & risk management, master data management, customer analytics, identity and access management, recommendation engine, privacy and risk compliance, and others. As per organization size, it is categorized into large enterprises and small & medium enterprises. According to industry vertical, it is fragmented into BFSI, retail & ecommerce, IT & telecom, healthcare & life science, government & public sector, media & entertainment, manufacturing, transportation & logistics, and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The report analyzes the profiles of key players operating in the market. These include DataStax, Franz Inc., Neo4j, Inc., Oracle Corporation, OrientDB, MongoDB, Objectivity Inc.,
Stardog Union Inc., Teradata Corporation, and Microsoft Corporation.
KEY BENEFITS FOR STAKEHOLDERS
The study provides an in-depth analysis of the global graph database market and current & future trends to elucidate the imminent investment pockets.
Information about key drivers, restraints, and opportunities and their impact analyses on the market is provided.
Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the global graph database industry.
The quantitative analysis of the market from 2018 to 2026 is provided to determine the market potential.
KEY MARKET SEGMENTS
BY DEPLOYMENT MODEL
BY TYPE OF DATABASE
BY ANALYSIS TYPE
Fraud Detection & Risk Management
Master Data Management
Identity and Access Management
Privacy and Risk Compliance
BY ORGANIZATION SIZE
Small & Medium Enterprises
BY INDUSTRY VERTICAL
Retail and Ecommerce
IT and Telecom
Healthcare and Life Science
Government and Public Sector
Media & Entertainment
Transportation & Logistics
Rest of Europe
Rest of Asia-Pacific
KEY MARKET PLAYERS
Stardog Union Inc.
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