Richmond, Jan. 17, 2024 (GLOBE NEWSWIRE) -- According to a research report "Graph Database Market”, by Component (Software & Services), Type Of Database (Relational (SQL), Non-Relational (No SQL)) Analysis Type (Connectivity Analysis, Community Analysis, Centrality Analysis) Deployment Mode (On Premise, Cloud Based) and Region - Global Forecast to 2030.
Global Graph Database Market Report Scope:
| Report | Details |
| Market size value in 2023 | USD 2.9 Billion |
| Market size value in 2030 | USD 4.7 Billion |
| CAGR (2023-2030) | 7.2% |
| Forecast Period | 2023–2030 |
| Historic Data | 2019 |
| Forecast Units | Value (USD Million/USD Billion) |
| Segments Covered | Offering, Component, End User and Region |
| Geographies Covered | North America, Europe, Asia Pacific, and RoW |
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| Sample of Companies Covered |
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TOC Covers in Depth & Breath on Graph Database Market
170 - Market Data Tables
65 - List of Figures
225 – Pages
The report includes Vendor Assessment (Company Profiles, Market Positioning, Strategies, Recent Developments, Capabilities & Component Components / Mapping), Technology Assessment (Developments & Economic Impact), Partner & Customer Ecosystem (Component Humanoid Robot, Proposition & Key Features) Competitive Index & Regional FootPrint by MarketDigits.
Market Overview
The global Graph Database market has witnessed significant growth in recent years. A graph database is a type of database management system that is designed to store and manage data in the form of a graph. Unlike traditional relational databases, which use tables to represent data and relationships, graph databases leverage nodes, edges, and properties to model and store information. Nodes represent entities, edges denote relationships between entities, and properties store additional information about nodes and edges. Graph databases are designed for handling complex relationships and interconnected data. This makes them valuable for applications such as social networks, fraud detection, recommendation engines, network analysis, and knowledge graphs.
Major Vendors in the Global Graph Database Market:
- Oracle Corporation
- IBM Corporation
- Amazon Web Services, Inc.
- DataStax
- Ontotext
- Stardog Union
- Hewlett Packard Enterprise
- ArangoDB
- Blazegraph
- Microsoft Corporation
- SAP SE
- Teradata Corporation
- Openlink Software
- TIBCO Software, Inc.
- Neo4j, Inc.
- GraphBase
- Cambridge Semantics
- TigerGraph, Inc.
- Objectivity Inc.
- Bitnine Co, Ltd.
- Franz Inc.
- Redis Labs
- Graph Story
- Dgraph Labs
- Eccenca
- Fluree
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Management & Analysis of complex relationships with datasets
One of the key driving factor behind the growth of the Graph Database market is the increasing need to manage and analyse complex relationships within data sets, common in applications such as social networks, supply chains, and fraud detection, thus driving the market for the graph database management. Graph databases excel in representing and querying interconnected data, making them essential for scenarios where relationships are central to insights.
Also with the growing demand for real-time analytics, especially in industries such as finance, healthcare, and cybersecurity, the adoption of graph databases has surged significantly. Their ability to quickly traverse relationships enables organizations to gain immediate insights, making them invaluable for applications that require timely decision-making and response. Unlike rigidly structured relational databases, graph databases offer a schema-less approach, allowing organizations to easily modify and extend their data models without significant disruptions.
Market Dynamics
Drivers:
- Fraud Detection and Analysis
- Cybersecurity threat detection.
- Semantic data integration.
- Healthcare network analysis & management of complex data relationships.
- Geospatial analysis and event impact analysis.
Opportunities:
- Healthcare Data Interoperability.
- Graph Databases in Quantum Computing.
- Energy Grid Optimization
- Graph-Based Semantic Search Engines & Robotics programming.
- Network and supply chain mapping.
Network & Supply Chain Mapping.
The advanced supply chains are vast and complex structure and are quite vulnerable to disruptions including the component shortages and the transportation delays. Graph databases acts like super-smart organizers for understanding relationships. In network mapping, like when we're dealing with computers, people, or anything connected, graph databases make things much clearer. Imagine you have a bunch of computers in an office, and they're all connected to each other. Each computer is a "node" in the graph, and the connections between them are the "edges." Now, let's say you want to find out which computer is connected to another, or you want to know if there's a weak link in the network. That's where a graph database works perfectly. For instance a shipping company might use a graph database to track the location of its ships and cargo in real-time.
Additionally these databases can be utilized for analyzing network traffic and identify security threats. This can help businesses to protect their networks from cyberattacks. For example, a security company might use a graph database to analyze network traffic to identify malicious activity Moreover a a shipping company might use a graph database to track the location of its ships and cargo in real-time.
North America dominates the market for Graph Database.
North America currently holds the largest share and is poised to maintain its dominance in the graph database market. These are propelled by several key factors that collectively establish the region as a powerhouse for technological innovation and adoption. Also North America's status as a global hub for technological innovation and research, with the United States leading the region. The region hosts a myriad of leading graph database vendors and technology startups, creating a concentrated environment of innovation that propels the development and widespread adoption of advanced technologies, notably graph databases.
The strong presence of tech giants, including industry behemoths like Amazon, Microsoft, and Google, further cements North America's position. These major players offer cloud platforms seamlessly integrated with graph database services, providing businesses with accessible and scalable solutions that facilitate the adoption and implementation of graph databases within their infrastructure.
The diverse applications of graph databases across industries in North America contribute significantly to their dominance. It has its presence right from fraud detection in financial services to supporting complex relationships in patient data within healthcare, the versatility of graph databases positions them as invaluable tools across different sectors.
The Software Segment is anticipated to hold the Largest Market Share during the Forecast Period.
The software segment dominates the market for the global graph database management. It has a wielding substantial influence by providing the essential technological framework for organizations to tap into the potential of graph databases. Serving as the bedrock for the creation, querying, and management of graph-based data structures, graph database software emerges as an indispensable component, empowering businesses to harness the intricate power of relationships within their datasets. This software not only facilitates the creation and management of nodes and edges but also integrates query languages like Cypher for Neo4j, enabling users to deftly retrieve and manipulate data with a distinct focus on relationships.
The software's capacity to augment data relationships and unveil concealed patterns fuels its adoption across industries. The pervasive influence of cloud-based solutions has further shaped the market dynamics, with organizations increasingly favoring cloud-based graph database solutions. This underscores the pivotal role of software in delivering scalable, accessible, and flexible database management solutions. Beyond foundational functionalities, graph database software emerges as a catalyst for innovation, enabling the development of applications endowed with advanced features like real-time analytics, personalized recommendations, and intricate network analysis.
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