Relational In-Memory Database Market Size & Industry Share - Growth Trends & Forecasts (2024 - 2031)

Based on the Deployment :

Based on the deployment, the market is bifurcated into cloud and on premise. The cloud segment accounted for a substantial revenue share in the year 2023. The cloud-based deployment offers a seamless collaboration along with fast and cost-effective access to the in-memory database by multiple users irrespective of the time and location of the user. Moreover, cloud-based relational in-memory databases offer various benefits such as minimal capital expense, rapid implementation, ease of utilization and integration, faster processing, and higher scalability. The above benefits of cloud-based deployment are prime factors for driving its utilization in the deployment of the in-memory databases.

For instance, SAP offers SAP HANA relational in-memory database that offers flexible deployment in public or private cloud. SAP HANA offers advanced analytics, search, and data integration capabilities for all types of structured and unstructured data. Thus, the increasing availability of the in-memory database for cloud-based deployment is a key factor proliferating the expansion of the segment.

As per the analysis, the on premise segment is anticipated to register significant CAGR expansion during the forecast period. On-premise deployment enables enterprises to manage, and have complete control over its integrations, and maintain tighter control over the application's security aspects as compared to cloud-based deployments. Moreover, the benefits of on premise deployment such as higher security, privacy, lower network bandwidth costs, and more control over server hardware are key factors determinants for increasing its utilization in the deployment of the in-memory databases.

For instance, Teradata is a provider of the in-memory database that offers on premise deployment of its database to deliver maximum security and high performance. Thus, the rising prevalence of this in-memory database providers offering on premise deployment options is a primary factor anticipated to drive the expansion of the market during the forecast period.

Based on the Enterprise Size :

Based on the enterprise size, the market is segregated into large enterprise and small & medium enterprise. The large enterprise segment accounted for the largest revenue share in the year 2023. Large enterprises refer to companies that have an above-average business size, perform large operations, and have high economies of scale. Large enterprises primarily comprise of a larger workforce, generate a high amount of revenue, and have a greater competitive capacity in comparison to small and medium enterprises. Moreover, large enterprises operating in Relational In-Memory Database industry often target national and international markets for delivery of advanced design and manufacturing services.

For instance, Oracle, SAP, and Intel Corporation are few of the large enterprises that offer this in-memory database for BFSI, retail, healthcare, and other industrial sectors. Thus, the prevalence of large enterprises operating in the in-memory database sector is a key factor driving the expansion of the segment.

Small & medium enterprise segment is expected to witness fastest CAGR expansion during the forecast period. Small and medium enterprises refer to companies that maintain revenues, workforce, and assets below a certain threshold. SMEs often account for the majority of the businesses that are operating across the world. SMEs are segregated from large enterprises because it operates differently with more simple operations.

For instance, Volt Active Data Inc. is a U.S.-based medium size enterprise operating in the relational in-memory database sector. The company's in-memory database offers real-time data processing with high scalability, accuracy, and resiliency. Thus, the rising development of small & medium enterprises operating in the in-memory database sector is projected to boost the expansion of the segment during the forecast period.

Based on the Application :

Based on the application, the market is classified into analytics, supply chain management, fraud detection, and others. The analytics segment accounted for the largest revenue share of 39.54% in the year 2023. The in-memory database is primarily used for application in real-time analytics for improving business health and discovering insights for informed decision-making among business organizations. Moreover, as per the analysis, the in-memory database stores data in internal memory to accelerate data analysis and provide users with real-time insights, without compromising on performance. Additionally, the in-memory database is primarily used for application in real-time analytics in multiple industries including BFSI, healthcare, retail, and others.

For instance, Oracle offers in-memory database in its portfolio that is integrated with a range of features for real-time analytics application with improved performance and scalability. Hence, the rising development of this in-memory database market trends for analytics application is a prime factor fostering the expansion of the market.

Fraud detection segment is expected to witness fastest CAGR growth during the forecast period. The in-memory database is often used for fraud detection application, particularly in the banking and financial sector. The in-memory database enables banking and financial institutions to monitor credit transactions and predict or detect fraudulent transactions.

For instance, Terdata offers in-memory database solution for fraud detection and prevention application for banking and financial institutions. The company's in-memory database is optimized for utilization by financial institutions to automate risk and fraud detection for increasing customer retention. Thus, the increasing utilization of this in-memory database for fraud detection application in BFSI institutions is anticipated to boost the market expansion during the forecast period.

Based on the End-User :

Based on the end-user, the market is segregated into BFSI, healthcare, retail & e-commerce, manufacturing, and others. The BFSI segment accounted for the largest revenue share in the year 2023. Factors including the rising digitalization of the BFSI sector, the prevalence of substantial number of banking/financial institutions, and rising need for efficient fraud detection and monitoring solutions in BFSI firms are crucial aspects driving the expansion of the BFSI segment.

For instance, according to the Canadian Bankers Association, the banking sector in Canada consisted of 5,711 bank branches in 2021. Therefore, the prevalence of significant number of banking firms is driving the market demand for The in-memory database for fraud detection and monitoring application, in turn proliferating the expansion of the market.

Retail & e-commerce segment is expected to witness fastest CAGR during the forecast period. The expansion of retail & e-commerce segment is primarily driven by multiple factors including expansion of retail enterprises, increasing consumer preference for online shopping, and growing need for retail warehousing and management solutions by retail enterprises among others.

For instance, according to Europe E-commerce Report 2022, the sales volume of online retail sector in Hungary was valued at approximately USD 3.7 billion in 2021, with online orders reaching up to 68.9 million in total. Thus, the growing retail & e-commerce sector is increasing the adoption of the in-memory database for facilitating supply chain management while driving operational efficiency and higher sales volume, in turn boosting the market growth during the forecast period.

Based on the Region :

The regional segment includes North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.

Asia Pacific accounted for the largest relational in-memory database market share of USD 886.19 Million in 2023 and is expected to reach USD 3,178.76 Million by 2031, registering the highest CAGR of 17.3% during the forecast period. In addition, in the region, the China accounted for the maximum revenue share of 31.5% in the same year.

As per the relational in-memory database market analysis, the growing pace of industrialization and development is creating lucrative opportunities and trends for the relational in-memory database market trends in the Asia-Pacific region. Moreover, the trends of BFSI, manufacturing, and other industries is among the prime factors boosting the relational in-memory database market trends in the Asia-Pacific region.

For instance, according to Invest India, there are approximately 123,000 bank branches across India as of March 2022. The in-memory database is often used in BFSI sector for monitoring credit transactions and predicting or detecting fraudulent transactions. Therefore, the demand of banking/financial institutions is projected to drive the relational in-memory database market growth in the Asia-Pacific region during the forecast period.

North America is expected to register CAGR of 16.8% during the forecast period. The adoption of this in-memory database in the North American region is primarily driven its usage in retail & e-commerce, BFSI, healthcare, and other sectors.

For instance, according to the U.S. Census Bureau of the Department of Commerce, the retail e-commerce sector in the United States was valued at USD 227.58 billion during the second quarter of 2023, representing a significant growth of 7.5% in comparison to USD 258.61 billion during the second quarter of 2022. Thus, the growth of retail & e-commerce sector is increasing the adoption of this in-memory database for facilitating supply chain management along with driving operational efficiency and higher sales volume, in turn fostering the market growth in North America. Further, rising investments in BFSI and healthcare sectors is projected to drive the market growth in North America during the forecast period.