Increasing need for better response time and accuracy to discover new data correlations is the key growth driver for the graph database market
The graph database market size is expected to grow from USD 821.8 million in 2018 to USD 2,409.1 million by 2023, at a Compound Annual Growth Rate (CAGR) of 24.0% during the forecast period. Some of the key drivers for the graph database market include enterprises’ increasing demand to have better response time and accuracy to discover new data corelations, and the advent of AI-enhanced graph database software and services.
However, lack of technical expertise and high setup costs associated with graph dataabases are restraining the growth of graph database market.
Risk Management and Fraud Detection is estimated to hold the largest market size in 2018 in the graph database market.
Fraud detection applications, through their real-time, near-real-time, and batch analysis of users’ activities, assist companies in safeguarding their customers and enterprise information, assets, accounts, and transactions. To address frauds and the related risks, enterprises use Transaction Monitoring Systems (TMS) that are based on relational databases. However, due to TMS’ linear and discrete analysis approach, they usually help in spotting trends and incidents post their occurrence on a limited basis. This is where graph database tools and services really add value and enhance the entire risk and fraud management process. Moreover, these tools and services add an additional security layer to its architecture. Graph database tools assist in identifying individual data points and the links between them. Furthermore, these tools enable the rapid extraction of new insights from large and complex databases to help reveal unknown interactions and relationships, quickening the entire process of execution.
Asia Pacific (APAC) is expected to grow at the highest rate during the forecast period in the graph database market by region.
APAC is expected to grow at the highest CAGR and estimated to have an immense potential for the growth of the graph database market in the coming years. Many Asian countries, including Singapore and China, are leveraging information-intensive technologies to gain a competitive edge over other players. They are digitizing rapidly and promoting the emerging technologies, such as mobility, IoT, cloud, BI, and analytics. This trend provides significant opportunities to grow for vendors of graph database tools and services in this region. The rapid digitization has resulted in the production of large volumes of unstructured data. The region has shown an unexplored potential for the adoption of data security solutions, which can be attributed to the evolving regulations that are encouraging many multinational operators to enter the graph database market for business expansion.
In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews were conducted with the key people.
The break-up of the profile of the primary participants is as follows:
- By Company: Tier 1 – 15 %, Tier 2 –32%, and Tier 3 –53%
- By Designation: C level – 38%, Director level – 30%, and Others – 32%
- By Region: North America – 20%, Europe – 38%, APAC – 32%, and RoW – 10%
The graph database market comprises following major vendors:
1. IBM (US)
2. Microsoft (US)
3. Oracle (US)
4. AWS (US)
5. Neo4j (US)
6. OrientDB (UK)
7. TIBCO Software (US)
8. Franz (US)
9. Teradata Corporation (US)
10. MongoDB (US)
11. OpenLink Software (US)
12. MarkLogic (US)
13. TigerGraph (US)
14. DataStax (US)
15. Ontotext (Bulgaria)
16. Stardog (US)
17. Cray (US)
18. ArangoDB (Germany)
19. Sparcity Technologies (Spain)
20. Memgraph (UK)
21. Bitnine (Korea)
22. Objectivity (US)
23. Cambridge Semantics (US)
24. Fluree (US)
25. Blazegraph (US)
The report segments the graph database market by application (customer analytics, risk management and fraud detection, recommendation engines, and others), type (RDF and property graph), components (tools and services), deployment models (on-premises and on-demand), organization sizes (large enterprises and SMEs), verticals (BFSI, telecom and IT, retail and eCommerce, healthcare and life sciences, manufacturing, government and public, transportation and logistics, energy and utilities, and others), and regions (North America, Europe, APAC, MEA, and Latin America).
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