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Global Graph Database Market – Industry Trends and Forecast to 2030

  • ICT
  • Upcoming Report
  • Dec 2022
  • Global
  • 350 Pages
  • No of Tables: 220
  • No of Figures: 60

Global Graph Database Market – Industry Trends and Forecast to 2030

Market Size in USD Billion

CAGR - % Diagram

Diagram Forecast Period 2022–2030
Diagram Market Size (Base Year) USD 1938.20 Million
Diagram Market Size (Forecast Year) USD 7384.79 Million
Diagram CAGR %

Global Graph Database Market, By Type (Resource Description Framework (RDF), Labeled Property Graph (LPG)), Application (Fraud Detection, Prevention, Recommendation Engine), Database (Relational (SQL), Non-relational (NoSQL)), Deployment Model (On-premise and Cloud), Analysis Type (Path Analysis, Connectivity Analysis, Community Analysis and Centrality Analysis), Size (Large Enterprises, Small and Medium Enterprises), Component (Software, Services), End User (Banking, Financial Services and Insurance, Telecom and IT, Healthcare and Lifesciences, Transportation and Logistics, Retail and E-commerce, Energy and Utilities, Government and Public, Manufacturing, Others) – Industry Trends and Forecast to 2030.

Graph Database Market Analysis and Size

Early adoption of graph database tools and rising industry alliances with many technology companies to deliver data processing and quick analytics solutions. The early stage of technological advancement established fin-tech solutions, and enhancements in information technology are all highly contributing to the growth of this market. Moreover predicted to support market growth due to the uptake of Internet of Things (IoT) and artificial intelligence (AI) devices. As a result of this, there is expected to be a substantial rise in demand for chart database solutions due to augmented investments in cutting-edge technologies such as machine learning (ML) in the coming years.

Data Bridge Market Research analyses that the graph database market is expected to reach USD 7384.79 million by 2030, which is USD 1938.20 million in 2022, at a CAGR of 18.20% during the forecast period. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

Graph Database Market Scope and Segmentation

Report Metric

Details

Forecast Period

2023 to 2030

Base Year

2022

Historic Years

2021 (Customizable to 2015 - 2020)

Quantitative Units

Revenue in USD Million, Volumes in Units, Pricing in USD

Segments Covered

By Type (Resource Description Framework (RDF), Labeled Property Graph (LPG)), Application (Fraud Detection, Prevention, Recommendation Engine), Database (Relational (SQL), Non-relational (NoSQL)), Deployment Model (On-premise and Cloud), Analysis Type (Path Analysis, Connectivity Analysis, Community Analysis and Centrality Analysis), Size (Large Enterprises, Small and Medium Enterprises), Component (Software, Services), End User (Banking, Financial Services and Insurance, Telecom and IT, Healthcare and Lifesciences, Transportation and Logistics, Retail and E-commerce, Energy and Utilities, Government and Public, Manufacturing, Others)

Countries Covered

U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America

Market Players Covered

Teradata (U.S.),  Hewlett Packard Enterprise Development LP (U.S.), IBM Corporation (U.S.), Microsoft (U.S.), Siemens AG (Germany), ANSYS, Inc (U.S.), SAP SE (Germany), Oracle (U.S.), Robert Bosch GmbH (Germany), Swim.ai, Inc. (U.S.)., Atos S.E. (France), ABB (Switzerland), KELLTON TECH (India), AVEVA Group plc (U.K.), DXC Technology Company (U.S.), Altair Engineering, Inc (U.S.), Hexaware Technologies Limited (India), Tata Consultancy Services Limited (India), Infosys Limited (India), NTT DATA, Inc. (Japan), TIBCO Software Inc. (U.S.), Redis Ltd (U.S.)

Market Opportunities

  • Increasing adoption of artificial intelligence (AI)-based graph database services and tools.
  • Growing demand for low-latency query processing solutions

Market Definition

Graph Database refers to a type of a database which uses graph structures for semantic queries with nodes, edges and properties to store and represent the data. Each edge represents a connection or relationship and each node represents an entity between two nodes. Graph databases are those technologies that translate the relational online transaction processing (OLTP) databases.

Graph Database Market

Drivers

  • Increasing demand for solutions with the capability to process low-latency queries

Graph database tools and services are extensively being used all over the globe, to the extent that numerous legacy database providers are endeavoring to assimilate graph database schemas into their main relational database infrastructures. Whereas, in theory the strategy might seem to save money, but actually it might degrade and slow down the performance of queries run beside the database. A graph database is altering traditional brick-and-mortar trades into digital business powerhouses in the terms of digital business activities. Therefore, increasing demand for solutions with the capability to process low-latency queries is anticipated to drive the growth rate of the market

  • Growing usage of graph database technology

Manufacturers extensively use graph database technology, particularly for business data management, with applications in numerous industries and sectors. The graph database technology has a numerous advantages as compared to other database systems, for resolving problems that arise while evaluating complicated and large data. These systems have capacity to s manage and scale massive data or information sets that come naturally.

Opportunities

  • Growing demand for low-latency query processing solutions

Businesses encounter problems when storing massive volumes of connected data in a database which is not suitable for any precise purpose. Now businesses deploy a real-time recommendation system that can handle low-latency queries rather than cumbersome batch process on top of a common relational database. It considerably outperforms conventional relational databases by enabling users to specially query prior purchases made by customers during an online visit to match session and historical data. There is less latency by using a graph database. Moreover, millions of connected records can be browsed with a reliable response time irrespective of database size meanwhile the links and nodes "point" to one another. To attain low latency, queries are divided into sub-queries that run instantaneously. Thus, growing demand for low-latency query processing solutions will create immense opportunities for market growth.

Restraints

  • Complex programming and standardization

While graph databases are technically NoSQL databases that must run on a single server in practice because these databases cannot be distributed in a low-cost cluster. This is what causes a network's performance to rapidly decline. Another major disadvantage is that the developers must write their inquiries in Java as there is no SQL to save data from graph databases, which necessitates hiring expensive programmers. All these are some of the major factors restraining the market's growth.

This graph database market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the graph database market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Covid-19 Impact Analysis on Global Graph Database Market

The outbreak of COVID–19 pandemic has transformed the dynamics of business operations globally and had a significantly negative influence on businesses owing to lockdowns imposed by governments to control the spread of coronavirus. However, the outbreak of COVID–19 provided numerous opportunities for companies to expand and digitalize operations across borders because implementation and adoption of technologies such as predictive analysis, Internet of Things (IoT), big data, Artificial Intelligence (AI), and blockchain technology augmented during the initial lockdowns. However, with the introduction of vaccinations, companies operating in such industries are anticipated to attract considerable investments because graph database solutions have gained more popularity across numerous business operations over the forecast period.

Recent Development

  • In 2021, Neo4j launched its new graph database, version 4.3 with incremental upgrades that highlight prior discoveries. As a result of enhanced relationship property indexes and smart IO scheduling, the most current version comprises relationship chain locking for faster write graph data science, transaction speed, and parallelized backup.
  • In 2021, DataStax, Inc. announced the acquisition of Kafkaesque Technologies Inc., a cloud messaging service completely driven and managed by Apache Pulsar, to speed the delivery of open-source, cloud-native and scale-out streaming of business events for advanced data applications. This acquisition allows companies to provide modern data applications with unlimited scaling, cloud hosting and rapid development speed.

Global Graph Database Market Scope

The graph database market is segmented on the basis of type, application, database, deployment model, analysis type, size, component and end user. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Type

  • Resource Description Framework (RDF)
  • Labeled Property Graph (LPG)

 Application

  • Fraud Detection
  • Prevention
  • Recommendation Engine
  • Database (Relational (SQL)
  • Non-relational (NoSQL)

Deployment Model

  • On-premise
  • Cloud

Analysis Type

  • Path Analysis
  • Connectivity Analysis
  • Community Analysis and Centrality Analysis

Size

  • Large Enterprises
  • Small and Medium Enterprises

Component

  • Software
  • Services
  • Professional Services
  • Managed Services

 End User

  • Banking, Financial Services and Insurance
  • Telecom and IT
  • Healthcare and Lifesciences
  • Transportation and Logistics
  • Retail and Ecommerce
  • Energy and Utilities
  • Government and Public
  • Manufacturing
  • Others

Graph Database Market Regional Analysis/Insights

The graph database market is analyzed and market size insights and trends are provided by country, type, application, database, deployment model, analysis type, size, component and end user as referenced above.

The countries covered in the graph database market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

North America dominates the graph database market in terms of revenue and market share owing to the presence of well-established fintech solution and early growth of the technology. Furthermore, advancements in information technology will further boost the market growth in this region. 

Asia-Pacific will continue to project the highest compound annual growth rate during the forecast period of 2023-2030 because opportunities for the smaller graph database sellers to launch graph database solutions for many sectors have considerably increased in this region.

The country section of the report also provides individual market impacting factors and changes in market regulation that impact the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of Global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.   

Competitive Landscape and Graph Database Market Share Analysis

The graph database market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, Global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to graph database market.

Some of the major players operating in the graph database market are:

  • Teradata (U.S.)
  • Hewlett Packard Enterprise Development LP (U.S.)
  • IBM Corporation (U.S.)
  • Microsoft (U.S.)
  • Siemens AG (Germany)
  • ANSYS, Inc (U.S.)
  • SAP SE (Germany)
  • Oracle (U.S.)
  • Robert Bosch GmbH (Germany)
  • Swim.ai, Inc. (U.S.)
  • Atos S.E. (France)
  • ABB (Switzerland)
  • KELLTON TECH (India)
  • AVEVA Group plc (U.K.)
  • DXC Technology Company (U.S.)
  • Altair Engineering, Inc (U.S.)
  • Hexaware Technologies Limited (India)
  • Tata Consultancy Services Limited (India)
  • Infosys Limited (India)
  • NTT DATA, Inc. (Japan)
  • TIBCO Software Inc. (U.S.)


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Research Methodology:

Data collection and base year analysis are done using data collection modules with large sample sizes. The stage includes obtaining market information or related data through various sources and strategies. It includes examining and planning all the data acquired from the past in advance. It likewise envelops the examination of information inconsistencies seen across different information sources. The market data is analysed and estimated using market statistical and coherent models. Also, market share analysis and key trend analysis are the major success factors in the market report. To know more, please request an analyst call or drop down your inquiry.

The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market and primary (industry expert) validation. Data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Patent Analysis, Pricing Analysis, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.

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Data Bridge Market Research is a leader in advanced formative research. We take pride in servicing our existing and new customers with data and analysis that match and suits their goal. The report can be customized to include price trend analysis of target brands understanding the market for additional countries (ask for the list of countries), clinical trial results data, literature review, refurbished market and product base analysis. Market analysis of target competitors can be analyzed from technology-based analysis to market portfolio strategies. We can add as many competitors that you require data about in the format and data style you are looking for. Our team of analysts can also provide you data in crude raw excel files pivot tables (Fact book) or can assist you in creating presentations from the data sets available in the report.

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FREQUENTLY ASK QUESTIONS

The Graph Database Market size will be worth USD 7384.79 million by 2030 during the forecast period.
The Graph Database Market growth rate is 18.20% during the forecast period.
The Growing usage of graph database technology and Increasing demand for solutions with the capability to process low-latency queries are the growth drivers of the Graph Database Market.
The type, application, database, deployment model, analysis type, size, component and end user are the factors on which the Graph Database Market research is based.
The major companies in the Graph Database Market are Teradata (U.S.), Hewlett Packard Enterprise Development LP (U.S.), IBM Corporation (U.S.), Microsoft (U.S.), Siemens AG (Germany), ANSYS, Inc (U.S.), SAP SE (Germany), Oracle (U.S.), Robert Bosch GmbH (Germany), Swim.ai, Inc. (U.S.)., Atos S.E. (France), ABB (Switzerland), KELLTON TECH (India), AVEVA Group plc (U.K.), DXC Technology Company (U.S.), Altair Engineering, Inc (U.S.), Hexaware Technologies Limited (India), Tata Consultancy Services Limited (India), Infosys Limited (India), NTT DATA, Inc. (Japan), TIBCO Software Inc. (U.S.), Redis Ltd (U.S.).
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