The In-Memory Analytics by The Business Research Company provides market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).
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According to The Business Research Company’s In-Memory Analytics, The in-memory analytics market size has grown exponentially in recent years. It will grow from $4.52 billion in 2023 to $5.66 billion in 2024 at a compound annual growth rate (CAGR) of 25.1%. The growth in the historic period can be attributed to complex data structures, enterprise focus on performance, need for real-time insights, demand for interactive data exploration, rise of advanced analytics.
The in-memory analytics market size is expected to see exponential growth in the next few years. It will grow to $14.43 billion in 2028 at a compound annual growth rate (CAGR) of 26.4%. The growth in the forecast period can be attributed to increasing growth in real-time analytics applications, in-memory analytics for data lakes, enhanced security and data protection, cross-platform compatibility, edge computing and decentralized analytics.. Major trends in the forecast period include integration with cloud services, integration with iot analytics, automated analytics and machine learning, continuous innovation in data storage and processing, real-time data processing.
The growing volume of data is expected to drive the growth of the in-memory analytics market. Growing data volume is increasing demand for large space in the system’s memory which leads to obstruction and delay in the business process. In-memory analytics is used to minimise the data into samples or reduce the data to a small volume by not changing the actual meaning and increasing the query response time. For instance, the International Data Corporation (IDC), a US-based examiner of the consumer market, estimated that 64.2ZB of data was created or copied in 2020. The amount of data created throughout the next five years will be larger than twice the volume of data created since the advent of digital storage. This is likely to drive the in-memory analytics market growth during the forecast period.
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The in-memory analytics market covered in this report is segmented –
1) By Component: Solution, Service
2) By Organization Size: Large Enterprises, Small and medium Enterprises (SME’s)
3) By Deployment Mode: On-premise, Cloud-Based
Technological advancement is a growing trend that is gaining key popularity in the in-memory analytics market. The companies operating in the in-memory analytics market are developing advanced technologies that will help in reducing the time for operation and complexity of the data by providing an enhanced product to their clients. For instance, In December 2021, GigaSpaces, a US-based software company, announced the launch of the InsightEdge portfolio, a new set of in-memory computing platforms that are designed to drive the enterprise digital transformation with unique speed, performance, and scale. Combined with the AIOps functionality, GigaSpaces will deliver effortless management and deployment of a portfolio of software platforms that meet the most stimulating analytics processing and enterprise data needs. AIOps refers to artificial intelligence for IT operations that provides analytics technology and enhances IT operations.
The in-memory analytics market report table of contents includes:
- Executive Summary
- In-Memory Analytics Market Characteristics
- In-Memory Analytics Market Trends And Strategies
- In-Memory Analytics Market – Macro Economic Scenario
- Global In-Memory Analytics Market Size and Growth
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- Global In-Memory Analytics Market Competitive Benchmarking
- Global In-Memory Analytics Market Competitive Dashboard
- Key Mergers And Acquisitions In The In-Memory Analytics Market
- In-Memory Analytics Market Future Outlook and Potential Analysis
- Appendix
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