Graph Databases Statistics 2025

In an era where data reigns supreme, understanding the evolution and utilization of graph databases in 2025 is pivotal for navigating the contemporary business landscape. These databases, which emphasize the relationships between data points, are becoming increasingly crucial for businesses aiming to leverage complex, interconnected datasets. As organizations across various sectors strive for more intelligent and efficient ways to handle data, the significance of graph databases cannot be overstated. They offer an unprecedented capability to analyze connections and patterns, driving insights that were previously unattainable with traditional databases.

Key stakeholders who would find this data invaluable include technology leaders, data scientists, and strategic decision-makers across an array of industries such as finance, healthcare, retail, and social media. These statistics not only illuminate current trends but also forecast the trajectory of the industry, ensuring that these professionals can stay ahead of the curve. For companies, understanding the dynamic landscape of graph databases is critical to optimizing their data strategies, gaining competitive advantages, and ultimately achieving business success.

By delving into these statistics, stakeholders can craft informed strategies and make data-driven decisions that foster innovation and growth. In a world where the volume and complexity of data continue to expand, leveraging the insights from graph database trends is essential for any organization wishing to thrive in the rapidly evolving digital age.

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Top Graph Databases Statistics 2025

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General Database Information

• Amazon Relational Database Service (Amazon RDS) supports multiple SQL Server editions including 2014, 2016, 2017, and 2019 [?].
• Amazon RDS supports MySQL Community Edition versions 5.7 and 8.0 [1].
• Amazon RDS supports MariaDB Server versions 10.3, 10.4, 10.5, and 10.6 [1].
• The Database Management System (DBMS) market size was valued at USD 84.82 Billion in 2023 and is projected to reach USD 149.23 Billion by 2030, growing at a CAGR of 9.07% during the forecast period 2025-2030 [4].
• The global database management system (DBMS) market size was USD 4382.00 billion in 2022 and the market is expected to reach USD 6,240.31 billion in 2030, exhibiting a Compound annual growth rate (CAGR) of 4.5% during the forecast period [8].
• The global database management systems (DBMS) market size was worth around USD 63.50 billion in 2022 and is predicted to grow to around USD 152.36 billion by 2030 with a compound annual growth rate (CAGR) of roughly 11.56% between 2023 and 2030 [9].

Graph Database Specific Information

• Graph databases are ideal for storing complex multi-hop data sets such as IoT data, Geospatial, Recommendation engines, and data related to Social networks/Customer 365 [2].
• Graph databases can handle complex nested relationships with multiple hops [2].
• Researchers employed graph databases to analyze COVID-19 data effectively during the pandemic [5].
• Graph databases were used to visualize infection patterns, geographical spread, and containment measures of COVID-19 [5].
• Graph databases allow for discovering connections and patterns in social networks, IoT, big data, data warehouses, and complex transaction data for multiple business use cases including fraud detection in banking and customer 360 [6].
• Neo4j surpassed $100 million in revenue in 2021, placing it among the top 30 database suppliers [10].
• Graph technologies are expected to be used in 80% of data and analytics innovations by 2025, up from 10% in 2021 [10].
• Gartner predicts revenue from cloud in the overall DBMS market to exceed 50% by 2023 [10].
• Alibaba Cloud’s database revenues grew by over 50% year over year [10].
• Graph Data Science (GDS) is one of the fastest-growing segments of Neo4j’s business since early 2020 [10].
• The ISO standard for graph query language (ISO/IEC 39075) is expected to be ready by the end of 2023 [10].
• In 2018, AWS released its Amazon Neptune product, making graph database technology widely available to businesses [14].
• Graph database usage is predicted to grow at 100% annually through 2022 to support complex data science and Big Data use cases [14].
• The graph database market is projected to grow at a CAGR of over 20% for the next five years [16].
• Graph analytics providers like Dgraph promise to eliminate up to 90% of backend code [14].
• The global graph database software market is expected to grow from $1.9 billion in 2021 to $5.1 billion by 2026 [18].
• Emergen Research projects the graph database software market to reach $11.25 billion by 2030 [18].
• GNNs (Graph Neural Networks) are becoming increasingly important, with almost half of last year’s top new AI research papers explicitly mentioning GNNs [19].
• Graph AI tools are expected to become more accessible to industry within the next two years [19].
• Graph databases have been instrumental in fraud detection, personalization, customer 360, knowledge graphs, and network management [20].

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Industry Applications & Use Cases

• JP Morgan Chase uses graph databases to help protect more than 60 million households in the U.S. [15].
• UnitedHealth Group (UHG) uses a massive graph database to track over 120 billion relationships among members, providers, claims, visits, prescriptions, procedures, and more [15].
• Some key supply-chain planning queries at Jaguar Land Rover (JLR) now take 45 minutes as opposed to weeks with graph databases [15].
• One large e-commerce company discovered 12 million new account connections across its five different retail websites using a graph database, estimating an efficiency saving of nearly $3 million and predicting a 17.6% increase in sales [15].
• Intuit’s graph-based machine learning has enabled the company to detect 50% more potential fraud events and reduced false positives by approximately the same percentage [15].

Performance And Benchmarking

• Memgraph 2.4 and Neo4j 5.1 community editions are benchmarked for performance limits [7].
• Most queries executed with Memgraph took between 1.09 to 11.32 milliseconds, while Neo4j took between 13 milliseconds to 135 milliseconds [7].
• Memgraph consumed 2.18% of the time budget for database latency, while Neo4j consumed 55% of the budget [7].
• Memgraph can handle 3.889 queries per second, while Neo4j can handle 37 queries per second [7].
• Neo4j uses up to 2.2GB of memory, while Memgraph uses around 400MB for the identical task [7].

Market Trends And Projections

• Database Management System Market size is poised to grow at a significant CAGR of 9.6% over 2024-2030 [3].
• The database management system market size is valued at USD 6.75 billion in 2023 [3].
• The report provides granular level information about the market size, regional market share, historic market (2019-2023), and forecast (2024-2030) [3].
• Global Database Management System Market Analysis, 2019 – 2023 and Forecast 2024 – 2030 [3].
• North America Database Management System Market, 2019 – 2023 and Forecast 2024 – 2030 [3].
• Middle East and Africa (MEA) Database Management System Market, 2019 – 2023 and Forecast 2024 – 2030 [3].

Technological Advancements

• The convergence of different database technologies, including online analytical processing (OLAP), online transaction processing (OLTP), and relational and NoSQL technologies was observed in 2022 [12].
• The MongoDB 6.0 NoSQL database provides users with analytics query acceleration [12].
• SingleStore updated its unified database to version 8.0 with new data query acceleration functionality specifically for JSON document data types [12].
• PostgreSQL 15 relational database update includes support for JSON [12].
• Observable raised $35.6 million for data collaboration capabilities [12].
• Dremio raised $160 million for data lakehouse capabilities [12].

Covid-19 Impact

• The COVID-19 pandemic has led to a sharp surge in demand for effective DBMS to handle data produced by remote workers and to provide remote access to corporate resources [3].
• Amidst the pandemic, researchers used graph databases to analyze COVID-19 data effectively [5].

Company Highlights

• Oracle announced Oracle Database 23c Beta on October 18, 2022—the latest version of the world’s leading converged database [3].
• Amazon RDS for MariaDB now supports M6i and R6i instances with new instance sizes up to 128 vCPUs and 1,024 GiB RAM as of April 26, 2022 [3].
• Oracle Corporation announced the Exadata database as a service and Exalogic middleware in April 2015 to enhance the processing of its databases and applications [13].
• Neo4j has been downloaded over 2 million times and has a large global community of developers [17].

Product Developments

• TigerGraph, provider of an advanced analytics and ML platform for connected data, announced a new version of TigerGraph Cloud with tools for visual graph analytics and machine learning [11].
• TigerGraph Cloud users can choose from 20+ starter kits for real-world industry use cases [11].

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