In-Memory Computing Companies | Forecast by 2033

08 Sep 2024

Table of Content

1. In-Memory Computing Market Growth, Trends and Report Highlights 2. Market Overview 3. In-Memory Computing Market Emerging Trends 4. Top Companies in the In-Memory Computing Market 5. Regional Insights 6. Market Potential & Growth Opportunity 7. In-Memory Computing Market Highlights 8. In-Memory Computing Market News

In-Memory Computing Market Growth, Trends and Report Highlights

The global in-memory computing market surpassed USD 18.04 billion in 2023 and is predicted to attain around USD 83.29 billion by 2033, growing at a CAGR of 16.53% during the forecast period. The rising demand for the in-memory computing market is due to a technological shift in terms of innovation, the transactional needs of potential customers, and the expanding need to store immense knowledge in a data bank to bring off accessible particulars with rapid computing operations.

Market Overview

To overcome the limitations associated with the data storage capacity, the urge for in-memory computing technology was raised. Insufficient storage ability cannot be enough criteria to store vast data from different operational tasks. To accomplish the broad vision of data repositories, information is stored in the computer’s RAM instead of hard drives or SSDs, which offers fast data processing with real-time data analytics. It eliminates the steps of handling and storing data in multiple ways, which could be time-consuming. In case of any fraud or sudden adverse events in industrial manufacturing, a quick decision-making approach can be chosen to eliminate the chances of loss by having a backup of resources and datasets.

Companies' adoption of digitization and industrial automation presents more advanced portfolios for the working system as well. It aims to manage industrial processes and machinery and, hence, drive the in-memory computing market by implementing different technologies, including the IoT. The Internet of Things (IoT) provides a platform to connect devices that create a high amount of data and allow effective workflows. For example, Siemens has put IoT into practice for its electronics manufacturing plants. IoT sensors can offer real-time process monitoring with the collection of data to analyze it further for any quality issues for an authentic launch of the final product.

This can promote the growth of important parameters related to business, healthcare, retail, telecommunication, government, finance, and banking by improving approaches toward risk assessment, compliance with regulatory authorities, safety and confidentiality, fraud case detection, workflow calculations, business management, and coordination. Along with these inventions and advancements, recent trends in working forces to work from home provide promising information for company targets and can also benefit by easily accessing the desired knowledge and statistics. Besides this, challenges for enterprises are the high costs of investment and dealing with ownership with strict compliance to laws due to the brilliant design features of these systems.

In-Memory Computing Market Emerging Trends

• The shift toward digital transformation across industries: To digitalize financial services, the software used is mobile banking apps and investment apps that help people invest in stocks, mutual funds, or cryptocurrencies. So this software also helps businesses manage accounts, process transactions, and analyze financial data. There comes the importance of data storage platforms in the computer’s memory.
• Advancement in RAM technology: In case of power loss, a retrieval of data is the concern. So, to store the last data used in power shortage times, NAND flash memory can be used which offers faster data conversion and information processing than hard disks. Dynamic Random Access Memory (DRAM) system memory storage is more rapid than Flash. 3D XPoint of another memory system is much quicker than Flash.
• HTAP-enabled in-memory computing: Hybrid transaction/analytical processing is the database that uses IMC to improve the performance of both transactional and analytical work and to store data in the working memory system itself. It eliminates the steps of working separately for both workflows.
• Adoption of technology in corporate sectors: Businessmen can profit by achieving efficient product launches, best marketing, reliable promotional strategies, and better financial income sources. Mobile banking or stock markets also demand these particulars to ensure trustful transactions, safe storage of investors’ data, and easy access to customers at any point of care.

Remarkable Transformation in HTAP-enabled IMC and Enormous Growth of Big Data Shaping the Achievements of Cutting-edge Technology

With time, people have the strong support of banking, e-commerce, and financial services for safe investment plans and promising business coordination. Online services are upgrading their demands simultaneously. Serverless SQL is a cloud-based query service that enables HTAP features significantly in automatically administrating computers to process queries.

Online transactional processing (OLTP) and online analytical processing (OLAP) both require specific performance parameters, which can be time-consuming to run separately. As a result, hybrid transaction/analytical processing (HTAP) can improve performance by allowing OLTP and OLAP operations to run smoothly on the same dataset. HTAP uses in-memory computing to store huge amounts of data in its system memory along with fast transactions per second and allowing problem-solving analytical work simultaneously.

• In April 2024, Microsoft Azure Synapse Analytics reported its remarkable advancements in HTAP features with serverless SQL pools after the incorporation of HTAP in combination with data warehousing and big data analytics. This enables real-time data processing and faster transactions with analytics on the same datasets.

In the era of modernization, real-time data analytics is emerging at its pace to provide authentic digitization for improving business worth and customer experience as well. Different e-commerce companies use various cloud computing platforms to perform specific functions related to transaction data, customer relationship management, web and data analytics, etc. For example, Amazon uses its principal AWS cloud for its research and development within the organization. Amazon also uses Microsoft Azure to work with Microsoft’s services and products, and Google Cloud is used for data analytics and machine learning. Embracing Big Data BigQuery Omni analytics minimizes the use of multiple cloud platforms and allows companies to perform well on their queries only with a single cloud as well.

• In March 2024, Google Cloud proclaimed its astonishing launch of BigQuery Omni which is an augmentation of its BigQuery Service that allows organizations to run their queries not only in Google Cloud but also in other cloud providers such as AWS, and Microsoft Azure. This enhances data consolidation and data investigation efficiency.

However, there can be a lack of skilled workforce to work with these cutting-edge technical assets. As per the World Economic Forum’s Future of Jobs 20184, there is a high need for specialists in AI and ML, automation, security, big data, etc. The security of data due to cyber theft and the lack of standards in the early adoption period are also major challenges in front of innovations. Besides this, financial services also face some challenges in dealing with fraud. Users can face issues with payments and purchases in any type of sector.

Due to this, organizations must have strong fraud detection systems to deal with fraudsters. Such systems drive the operation with real-time transaction risk-scoring algorithms. They can analyze users' personal account information, transaction details, locations, behavioral biometrics, etc. This sets up transparency between customers and vendors. Real-time decision-making, efficiency in working, and testing performance parameters are possible by adopting big data analytics. These big databases help in every way to go further with advanced tactics.

Top Companies in the In-Memory Computing Market

• Microsoft
• MongoDB
• HCL Technologies Limited
• Oracle Corporation
• SAP
• DataStax
• GridGain
• Aerospike
• Red Hat, Inc.
• ScaleOut Software, Inc.
• Pivotal Software, Inc.
• Altibase Corp.
• TIBCO Software Inc.
• Software AG

Recent Developments by HCL Technologies Limited

Recent Developments by Microsoft

Regional Insights

Asia Pacific is expected to host the fastest-growing in-memory computing market during the forecast period between 2024 and 2033 due to the rising adoption of digital technologies such as AI, big data, cloud computing, and machine learning to optimize business intelligence and customer experience. Across the region, there are several government initiatives to support digitalization and innovative projects that help the market to grow in demand and supply as well.

The Government of India launched The Digital India Program with the vision to develop core digital infrastructure with easy access to every citizen, to provide governance and services in high demand to empower citizens in digitalization. Increased online transactions, rising need for data security, and compliance of industries with legal regulations are driving the growth of the in-memory computing market.

Japan is progressive in cybersecurity and cyber defense strategies, which focus on special action plans for cybercrimes and the development of infrastructure by adopting a preventive approach to crimes.

China is proactive in boosting its computing plans by 2025 to upgrade national data centers. In educational sectors, it aims to upgrade the knowledge of students, and providing them with training on computers is one of the motives. It takes efforts to apply computing data centers in different sectors such as finances, transportation, etc.

North America dominated the in-memory computing market in 2023. The rising development is due to the adoption of modern technologies in various sectors and the presence of leading players in the market. There are major players as cloud platform providers, such as Amazon Web Services, Microsoft Azure, and Google Cloud, which offer in-memory computing solutions to organizations and corporate businesses. The top companies, such as Microsoft, Oracle, IBM, etc., are driving the successful impact of the computing technology.

• In April 2024, IBM Elastic Storage System 5000 was introduced to help an organization with a wide data storage capacity for their AI, cloud computing, high-performance computing, and analytics workloads. It enhances flexibility and transparency in workflows.

The U.S. National Science Foundation in collaboration with the U.S. Department of Energy (DOE) provides funds and resources for scientific advancements related to information communication technology. They run scientific computing programs to examine their correctness and to ensure their compliance with the policies and legislations.

Market Potential & Growth Opportunity

By using advanced in-memory databases, a customer experience can be better enhanced by optimizing web and data analytics. Businessmen can maintain better customer relationship management protocols to avoid any misconduct in the service. With a more advanced approach of scientists toward great research and development, in-memory computing is also raising its importance with its powerful datasets and outstanding features. Every citizen can benefit from this digital effort to educate and modernize themselves. With increasing support from the government for the success of technological innovation, the cost-effectiveness of data storage resources can also be reduced. The IoT applications also help to improve the scalability, performance, speed, reliability, and flexibility of the resources.

• In February 2024, Tech Mahindra announced its acceptance of in-memory computing technology features which particularly aim at strengthening data analytics in healthcare and telecommunication.
• In June 2023, it also launched a new feature named ‘Vision Amplifier,’ which is powered by Generative AI for smart computing projects and business analysis.

In-Memory Computing Market Highlights

In-Memory Computing Market News

• In December 2023, Samsung Electronics introduced Magnetoresistive Random Access Memory (MRAM) technology, which uses magnetic properties for data storage at high speed and can withstand for a long duration during computing operations. MRAM requires less power while working, and it can store data in power shortage, just like a flash memory. It takes efforts to combine memory and system to make next-generation AI- semiconductor chips.
• In October 2023, Tech Mahindra reported its advancement in cloud and edge computing features. The cloud is great for tasks like advanced analytics that use large amounts of historical data. Edge computing enables real-time AI-powered decision-making tasks by offering a high degree of data security.

Market Segmentation

By Component

• Solutions
• In-memory Database
• Online Analytical Processing
• Online Transaction Processing
• In-Memory Data Grid
• Data Streaming
• Services
• Professional Services
• Consulting
• System Integration And Implementation
• Managed Services

By Deployment Method

• Cloud
• On-premises

By Organization Size

• SMEs
• Large Enterprises

By Vertical

• BFSI
• IT & Telecom
• Retail & E-commerce
• Healthcare & Life Sciences
• Transportation & Logistics
• Government & Defense
• Energy & Utilities
• Media & Entertainment
• Others (Education, Manufacturing, Travel, & Hospitality)

By Applications

• Risk Management and Fraud Detection
• Sentiment Analysis
• Geospatial / GIS Processing
• Sales and Marketing Optimization
• Predictive Analysis
• Supply Chain Management
• Others (Image Processing, Route Optimization, Claim Processing & Modeling, & Trade Promotion Simulations)

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