In-Memory Database Market
Market Overview
As per the recent study, the global In-Memory Database Market Analysis in 2022 is witnessed at USD 5.00 billion and is expected to grow at a significant CAGR of 18.7% along with the market size of USD 32.2 Billion during the forecast period 2022-2030.
An in-memory database is a database technology that stores the data in the main memory as either single or distributed for promoting faster execution. This is specially designed for the workloads of different kinds like transactional, analytical, along operational ones. As this technology is used to reduce data latency, it is further highly demanded in data extraction and real-time processing. The in-memory database solutions are fulfilling the requirement of data analysis in real-time across the world. It attains a minimum response time and high throughput for performance-critical systems.
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This technology has various beneficial features like high stability, multi-user currency, faster transactions, big data management, no translation, real-time updates, and reduces IT costs. The major advantages of this technology are faster query response, proper processing, and encouraged self-service analytics. This technology is highly demanded in various applications like BFSI, Healthcare & Lifesciences, manufacturing, retail, IT & telecommunication, transportation, media & entertainment, consumer goods, energy & utilities, and others. The rise in web-based transactions and the improved rate of business analytics are accelerating market growth.
The In-memory database market opportunities are due to the introduction of technological developments and increasing demand from various industry verticals is enhancing the demand for in-memory databases by various government and private organizations is expanding the market growth.
Market Segmentation
The In-memory database market is segmented into six types based on the application, data type, deployment mode, processing type, organization size, and vertical.
Application Segmentation: The In-memory database market applications are analytics, reporting, transaction, and others.
Data Type Segmentation: By data type segment, the In-memory database market is trifurcated into NewSQL, NoSQL, and relational.
Deployment Segmentation: Based on the deployment mode segment, the market is sectioned into three forms on-cloud basis, on-demand basis, and on-premise basis.
Processing Type Segmentation: The In-memory database market by processing type is bifurcated into online transaction processing (OLTP), and online analytical processing (OLAP).
Organization Size Segmentation: Based on the organization size, the market is bifurcated into small & medium-sized enterprises and large enterprises.
Vertical Segmentation: By vertical, the In-memory database market is divided into various forms such as energy & utilities, government & defense, media & entertainment, transportation, IT & telecommunication, retail & consumer goods, healthcare, BFSI, and others.
Regional Analysis
Based on the latest report, the global In-memory database market based on the region is categorized into five major regions such as Asia-Pacific, North America, Europe, Latin America, and the Middle East & Africa. Out of these regions, North America is dominating the largest market share due to the rising demand for in-memory databases for transferring files quicker with technical expertise. Asia-Pacific is holding the second largest market share and is said to be the fastest-growing as it provides real-time intelligence analytics outsourcing facilities.
The In-memory database market prominent players are IBM Corporation (US), SAP SE (Germany), Microsoft Corporation (US), and Oracle Corporation (US).
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Industry News
As per the latest survey, the In-memory database market forecast states that this software is expected to grow at a significant rate due to developing a new product line, setting up a new joint venture, developing existing products, and innovations are expanding the market growth. Azure SQL database improves the performance of the organization.
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