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Graph Database Market Size is Projected To Reach USD 1546.5 Million By 2026 At A CAGR of 13.9% - Valuates Report

·8 min read

BANGALORE, India, Sept. 27, 2021 /PRNewswire/ -- Graph Database Market By Type - RDF, Property Graph, By Application -BFSI, Telecom and IT, Retail and E-commerce, Healthcare and Life Sciences, Manufacturing, Government and Public, Transportation and Logistics, Energy and Utilities, Others. Global Opportunity Analysis and Industry Forecast, 2021 - 2026. It is published in Valuates Reports under the Data Management Category.

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The global Graph Database market size is projected to reach USD 1546.5 million by 2026, from USD 603.4 million in 2019, at a CAGR of 13.9% during 2021-2026.

In computing, a graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph (or edge or relationship), which directly relates to data items in the store. The relationships allow data in the store to be linked together directly, and in many cases retrieved with one operation.

The major factor driving the growth of the Graph Database Market are:

The growth of the graph database market can be attributed to an increase in graph database application areas, an increase in connected data penetration to optimize marketing performance, a surge in graph database software adoption in the healthcare sector, and a rise in the need for better response time and accuracy to discover new data correlations, among other factors.

In comparison to other database solutions, graph database technology offers various advantages for solving challenges encountered while evaluating huge and complicated data. These advantages and systems are able to scale and handle enormous data sets. These features are in turn expected to drive the growth of the graph database market during the forecast period.

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A rising demand for solutions that can process low-latency queries is expected to drive the growth of the graph databases market. Companies have issues when it comes to storing large amounts of connected data in a database that isn't appropriate for the task at hand. Companies can use a real-time recommendation system built on top of a graph database capable of performing low-latency queries instead of a sophisticated batch process on top of a legacy relational database. It can be used to query consumers' past purchases during an online visit in a way that outperforms typical relational databases by matching historical and session data.

The emergence of open knowledge networks is expected to create a lucrative growth opportunity for the graph database market growth. Knowledge networks must have datasets, methods, and documentation to establish usability across applications, and interlink numerous disciplines to create a cross-domain knowledge network. Several knowledge graphs in this information network are still proprietary, and use by universities or researchers is usually prohibitively expensive. Owing to this scenario, various professionals from academia, government, and industry have invented the term "open knowledge network" to describe an open-source infrastructure that connects cross-domain data from relevant entities. An open knowledge graph containing all world knowledge is expressed as entities and relationships. The National Science Foundation in the United States has proposed the open knowledge network as one of the ten major ideas, and it is intended to drive the curation of reliable knowledge graphs/networks.

During the COVID-19 pandemic, the use of graph databases has increased. The need for graph database solutions and services, as well as the creation of digital infrastructures for large-scale technology deployments, has risen as a result of new habits such as work from home and social distancing. Thus the COVID-19 pandemic is expected to fuel the growth of the graph database market.

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North America is expected to hold the largest market share during the forecast period. On the other hand, the APAC region is expected to witness the highest CAGR. As a manufacturing powerhouse, APAC is projected to widely employ graph database solutions and services in order to keep costs down and export high-quality items to other nations.

Based on application, the BFSI is expected to be the most lucrative. Increased regulatory scrutiny, increased customer satisfaction, and perks such as risk management and customized solutions have all contributed to the BFSI segment's growth.

Based on type, RDF is expected to be the most lucrative segment. This growth of RDF is attributed to its capability of focusing on the information that is organized in a subject-predicate-object relationship.

Graph Database Market By Type

  • RDF

  • Property Graph

Graph Database Market By Application

  • BFSI

  • Telecom and IT

  • Retail and E-commerce

  • Healthcare and Life Sciences

  • Manufacturing

  • Government and Public

  • Transportation and Logistics

  • Energy and Utilities

  • Others

Graph Database Market By Region

  • North America

  • Europe

  • Asia-Pacific

  • Latin America

  • Middle East & Africa

Graph Database Market By Company

  • IBM

  • Microsoft

  • Oracle

  • AWS

  • Neo4j

  • Orientdb

  • Teradata

  • Tibco Software

  • Franz

  • OpenLink Software

  • Marklogic

  • Tigergraph

  • MongoDB

  • Cray

  • Datastax

  • Ontotext

  • Stardog

  • Arangodb

  • Sparcity Technologies

  • Bitnine

  • Objectivity

  • Cambridge Semantics

  • Fluree

  • Blazegraph

  • Memgraph

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