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In Memory Computing Market Size, Share | Growth Prediction - 2030
In Memory Computing Market Size, Share | Growth Prediction - 2030
In-memory computing is a type of purpose-built database that stores data in RAM rather than in databases hosted on disks. IMC provides super-fast performance, which aids businesses to enhance performance, quickly analyze huge volumes of data in real-time at very high speeds, and detect patterns.

In Memory Computing Market

Market Overview

The global In-Memory Computing Market is expected to register a CAGR of 12.16% from 2018 to 2026. The market should be worth USD 25.1 billion in 2026. 

In-memory computers differ from conventional computers because they (in-memory computers) store information in the RAM on their hard drives. Other computers use CDs and other external discs to store this type of information.

It’s this ability to store information internally that makes these types of computers extremely fast in performance. They’re also amazingly accurate in terms of storing, using and retrieving data. In-memory computers can also analyze key data at breakneck speed. 

There is one trait that separates in-memory computers from conventional computers. It’s the ability to detect patterns in key business data in real-time. Many businesses rely on these patterns and analyses when making strategic and/or key decisions.

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Segment Overview:

By Component:

This segment can be grouped as follows:

  • Solutions
  • Services 

The solution sub-segment can be further grouped into

  • In-memory database
  • In-memory data grid
  • Datastream processing

The in-memory database can be grouped further 

  • Online analytical processing
  • Online transaction processing

By services:

This segment can be grouped as follows:

  • Professional services
  • Managed services

The professional services sub-segment can be grouped further into:

  • Consulting
  • System integration
  • Implementation
  • Support
  • Maintenance

By application:

This segment can be grouped further into:

  • Risk management
  • Fraud detection
  • Sentiment analysis
  • Geospatial/GIS processing
  • Sales and marketing optimization
  • Predictive analysis
  • Supply chain management
  • Others

By deployment mode:

This segment can be grouped further into:

  • Cloud
  • On-premises

By organization size:

This segment can be further grouped into:

  • SMEs
  • Large enterprises

By Vertical:

This segment can be further grouped into:

  • BFST
  • IT & Telecoms
  • Retail and e-commerce
  • Healthcare and life sciences
  • Transportation and logistics
  • Government and defense
  • Energy and  utilities
  • Media and entertainment
  • Others
  • Education
  • Manufacturing
  • Travel and hospitality

Regional analysis:

The global in-memory computing market can be grouped into the following geographic regions:

  • Asia-Pacific
  • North America
  • The European Union
  • The Middle East and Africa
  • South America

In Memory Computing Market size

The North American region held the largest market share. The European Union came in third place, and the Asia-Pacific region comes in third place. The North American region is expected to continue to retain its number one position for the time period that this report covers.

The North American region is also expected to register a healthy CAGR for the time period that this report covers. What’s driving this phenomenal growth is a growing demand for advanced analytics platforms and technologies. 

Another key factor that’s driving growth in the region is the fact that most of the world’s major in-memory computing companies are concentrated in the North American region. 

That said, the Asia-Pacific region is projected to register the highest regional CAGR for the time period that this report covers. Rapid urbanization and modernization largely drive this.

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Industry news

  • Grid Gain integrated with Oracle cloud to strengthen the security of its in-memory computing platforms. The move is also intended to improve the quality of in-memory computing services.
  • TIBCO recently acquired a high-performance in-memory computing company called Snappy Data. the result was a unified and high-performing quality analytics system that companies can rely on.

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