28-Apr-2022 | Zion Market Research
The global graph database market was worth around USD 1827.5 million in 2021 and is estimated to grow to about USD 5996.24845178325 million by 2028, with a compound annual growth rate (CAGR) of approximately 21.9 percent over the forecast period. The report analyzes the digital remittance market’s drivers, restraints/challenges, and the effect they have on the demands during the projection period. In addition, the report explores emerging opportunities in the digital remittance market.
In computing, a graph database (GDB) is a database that uses graph structures for semantic queries with edges, nodes, and properties to represent and accumulate data. They are purpose-built to store and navigate relationships. Graph databases use nodes to store data units, and edges to store relationships between units. Because related nodes are physically linked in the database, accessing those relationships is as immediate as accessing the data itself. A graph database is built to handle highly connected data, and the increase in the volume and connectedness of today's data presents a tremendous opportunity for sustained market growth.
The need to incorporate real-time big data mining with visualization of results, increasing adoption of AI-based graph database tools and services to drive the market and growing demand for solutions that can process low-latency queries are some of the various factors that are expected to drive the adoption of graph database solutions and services. When it comes to digital business enterprises, a graph database is transforming the traditional brick-and-mortar companies into digital business centers. Companies face challenges with placing huge volumes of connected data in a database, which is not optimized for any desired purpose. Instead of employing a complex batch process on top of a legacy relational database, companies can use a real-time recommendation system built on top of a graph database capable of processing low-latency queries.
The global graph database market is segregated based on Component, Deployment Mode, Organization Size, Type, Application, and Vertical. Based on Component, the global market is distinguished into Software and Services. Based on Deployment Mode, the global market is distinguished into Cloud and On-premises. Based on Organization Size, the global market is distinguished into Large Enterprises, Small and medium-sized enterprises (SMEs). Based on Type, the global market is distinguished into RDF and Labeled Propert Graph. Based on Application, the global market is distinguished into Customer Analytics, Risk, Compliance and Reporting Management, Recommendation Engines, Fraud Detection and Prevention, Supply Chain Management, Operations Management and Asset Management, Infrastructure Management, IoT, Industry 4.0, Knowledge Management, Content Management, Data Extraction and Search, Metadata and Master Data Management, Scientific Data Management, Others (Chatbot, digital twin, scientific, Product and Technical Information Management, and Human Capital Management). Based on Vertical, the global market is distinguished into BFSI, Retail and eCommerce, Telecom and IT, Healthcare, Pharmaceuticals, and Life Sciences, Government and Public Sector, Manufacturing and Automotive, Media and Entertainment, Energy and Utilities, Travel and Hospitality, Transportation and Logistics, and Others.
North America leads the global graph database market because of the increasing technological advancements and the early adoption of these technologies in the region. The growing number of graph database players across regions and investments made by vendors are expected to fuel the market growth. The Asia Pacific region is expected to register a steady growth during the forecast period, as many Asian countries such as India, China, Japan, and South Korea are leveraging information-intensive technologies to gain a competitive edge over other players. The Middle East and Africa are likely to grow due to the increasing demand for enhanced data visualization tools. Lastly, Europe is also expected to drive growth due to the wide adoption of smart technologies that help users to get real-time data visualization.
Key players functioning in the graph database market include Oracle Corporation (US), IBM Corporation (US), Amazon Web Services, Inc. (US), DataStax (US), Ontotext (Bulgaria), Stardog Union (US), Hewlett Packard Enterprise (US), ArangoDB (US), Blazegraph (US), Microsoft Corporation (US), SAP SE (Germany), Teradata Corporation (US), Openlink Software (US), MarkLogic Corporation (US), TIBCO Software, Inc. (US), Neo4j, Inc. (US), GraphBase (Australia), Cambridge Semantics (US), TigerGraph, Inc. (US), Objectivity Inc. (US), Bitnine Co, Ltd. (US), Franz Inc. (US), Redis Labs (US), Graph Story (US), Dgraph Labs (US), Eccenca (Germany), and Fluree (US).
Browse the full “Graph Database Market By Component (Software and Services), By Deployment Mode (On-premise and Cloud), By Organization Size (Large Enterprises, Small and medium-sized enterprises (SMEs)), By Type (RDF and Labeled Propert Graph), By Application (Customer Analytics, Risk, Compliance and Reporting Management, Recommendation Engines, Fraud Detection and Prevention, Supply Chain Management, Operations Management and Asset Management, Infrastructure Management, IoT, Industry 4.0, Knowledge Management, Content Management, Data Extraction and Search, Metadata and Master Data Management, Scientific Data Management, Others (Chatbot, digital twin, scientific, Product and Technical Information Management, and Human Capital Management)), By Vertical (BFSI, Retail and eCommerce, Telecom and IT, Healthcare, Pharmaceuticals, and Life Sciences, Government and Public Sector, Manufacturing and Automotive, Media and Entertainment, Energy and Utilities, Travel and Hospitality, Transportation and Logistics, and Others).” Report at https://www.zionmarketresearch.com/report/graph-database-market
Recent Developments:
Global Graph Database Market is segmented as follows:
By Component
By Deployment Mode
By Organization Size
By Type
By Application
By Vertical
By Region
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