The Graph Database Market size is expected to grow from USD 1.0 billion in 2019 to USD 2.9 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 22.2% as per a report by MarketsandMarkets.
Why need to identify complex patterns at maximum scale is a good opportunity?
Organizations are beginning to take a deeper look at capturing data about continuous flowing data. The ability of organizations to act as soon as events are generated, improves operational responsiveness and organizational effectiveness. Integration of businesses with graph database tools and services provides flexibility to apply rich context to the events as they occur. Graph database can be used to improve operational efficiencies, reduce infrastructure costs, and provide faster insights and actions. Organizations in every industry have data available from applications, social media, sensors, devices, and websites. Analyzing this data in real time, rather than storing and analyzing it later, can provide critical, actionable insights in many operational and functional areas. Essentially, a graph database is all about extracting business value from data in motion, the same way traditional analytics tools make use of data at rest. Furthermore, a graph database should be a general-purpose solution that can be integrated with or embedded into other applications. Tight integration is required if the results derived are used to make real-time decisions or to take actions regarding customer service, security or fraud prevention, and product recommendations.
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How lack of technical expertise could pose a challenge?
Graph database tools and services provide a conclusive view of large data volumes in real time. The integration of the solutions offers a larger picture to decision-makers and provides actionable insights to boost the overall performance of the systems. Graph database solutions can be customized to enable integration with tools and services, depending on the level and nature of the analysis. Today’s business and user requirements demand applications that connect more and more of the world’s data, expect high levels of performance and data reliability. Graph database engines require a different approach to application development, a custom storage model, and special query tools. Additionally, large enterprises and SMEs need professional services to customize a particular product’s capability to meet the customer’s requirement. Since the graph database concept is in its growing phase, the availability of skilled labor is limited, and this can act as a restraint for the market growth. Companies should invest significantly in training and certifications for their workforce to effectively implement the insights received from large data volumes. Additionally, as retail organizations scale up their performance, the need for integrating data from various industry verticals across geographic locations become more necessary. The knowledge constraints and inadequate workforce skills may limit end users from adopting graph database software and associated services.
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The global graph database market size is projected to reach USD 2,409.1 million by 2023, growing at a Compound Annual Growth Rate (CAGR) of 24.0% during the forecast period (2018–2023). Major vendors in the graph database market include IBM (US), Microsoft (US), Oracle (US), AWS (US), Neo4j (US), OrientDB (UK), TIBCO Software (US), Franz (US), Teradata Corporation (US), OpenLink Software (US), MarkLogic (US), TigerGraph (US), DataStax (US), Ontotext (Bulgaria), Stardog (US), Cray (US), ArangoDB (Germany), Sparcity Technologies (Spain), Memgraph (UK), Bitnine (Korea), Objectivity (US), MongoDB (US), Cambridge Semantics (US), Fluree (US), and Blazegraph (US).
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