Global Sql in In-Memory Database Market
Global Sql in In-Memory Database Market

Sql in In-Memory Database Comprehensive Study by Deployment Mode (On-Premise, On-Demand), End Users (Banks, Retail, Healthcare, E-Commerce, Aviation, Others), Organization Size (Large Enterprises, Small and Medium Enterprises), Processing Type (Online Analytical Processing (OLAP), Online Transaction Processing (OLTP)) Players and Region - Global Market Outlook to 2026

Sql in In-Memory Database Market Segmented into XX Submarkets. | Forecast Years: 2021- 2026  

Oct 2021 Edition 207 Pages 218 Tables & Figures
  • Summary
  • Market Segments
  • Table of Content
  • List of Tables & Figures
  • Companies Mentioned
Industry Background:
In-memory databases, in a contrast to databases that store data on disc or SSDs, are purpose-built databases that rely mostly on memory for data storage. By eliminating the need to access drives, in-memory data stores are designed to provide fast reaction times. In-memory databases risk losing data if a process or server fails since all data is stored and managed completely in the main memory. In-memory databases can persist data on discs by logging each activity or storing snapshots. In-Memory OLTP in SQL Server and SQL Database is the most advanced option for enhancing transaction processing, data intake, data load, and transient data scenarios.This growth is primarily driven by Faster Data Processing, Multi-User Concurrency and A Huge Amount of Data Is Being Produced by Various Industries.

Globally, a noticeable market trend is evident Rapid Development of SQL/NoSQL . Major Players, such as Amazon Web Services (United States), IBM (United States), Oracle (United States), SAP (Germany), Microsoft (United States), Teradata (Germany), Software AG (Germany), Kognitio (United Kingdom), ENEA (Sweden) and Altibase (South Korea) etc have either set up their manufacturing facilities or are planning to start new provision in the dominated region in the upcoming years.

Key Developments in the Market:
In February 2021 Amazon Web Services Released a Statement Announcing the Acquisition of DataRow as the company's primary product is a Web-based client for Amazon Redshift, a cloud data warehouse. This Acquisition provides a unique tool in Amazon Redshift that allows data analysts to easily explore and visualize data. Users can create tables, import data, write queries, run visual analyses, and collaborate with others to exchange SQL code, discoveries, and analysis.

Market Drivers
  • Faster Data Processing
  • Multi-User Concurrency
  • A Huge Amount of Data Is Being Produced by Various Industries

Market Trend
  • Rapid Development of SQL/NoSQL
  • Rapid Prevalence of Hybrid Transactional and Analytical Processing (HTAP)

Restraints
  • Data Security Concerns Due to Cyber Crime
  • Memory Space Constraints

Opportunities
Low Latency, High Throughput, Faster Response Time and Zero or No Lock Amplification Management is Through an Optimistic Concurrency Model, Better Concurrency Management
Challenges
There is no Concept of HEAP and In-Memory OLTP Does Not Have the Ability to Lock Records Like Regular SQL Server Queries Do, Save for an Application Lock

AMA Research follow a focused and realistic research framework that provides the ability to study the crucial market dynamics in several regions across the world. Moreover, an in-depth assessment is mostly conducted by our analysts on geographical regions to provide clients and businesses the opportunity to dominate in niche markets and expand in emerging markets across the globe. This market research study also showcase the spontaneously changing Players landscape impacting the growth of the market. Furthermore, our market researchers extensively analyse the products and services offered by multiple players competing to increase their market share and presence.

Customization in the Report
AMA Research features not only specific market forecasts, but also include significant value-added commentary on:
- Market Trends
- Technological Trends and Innovations
- Market Maturity Indicators
- Growth Drivers and Constraints
- New Entrants into the Market & Entry/Exit Barriers
- To Seize Powerful Market Opportunities
- Identify Key Business Segments, Market Proposition & Gap Analysis

Against this Challenging Backdrop, Sql in In-Memory Database Study Sheds Light on
— The Sql in In-Memory Database Market status quo and key characteristics. To end this, Analyst at AMA organize and took survey of the Sql in In-Memory Database industry Players. The resultant snapshot serves as a basis for understanding why and how the industry can be expected to change.
— Where Sql in In-Memory Database industry is heading and what are the top priorities. Insights are drawn from financial analysis, the survey and interviews with key executives and industry experts.
— How every company in this diverse set of Players can best navigate the emerging competition landscape and follow a strategy that helps them position to hold value they currently claim, or capture the new addressable opportunity.

Frequently Asked Questions (FAQ):

1. What are the years considered in the Sql in In-Memory Database Market?
Historical year: 2016-2020; Base year: 2020; Forecast period: 2021 to 2026

2. Who are the key players profiled in the Sql in In-Memory Database Market?
Companies that are profiled in Global Sql in In-Memory Database Market are Amazon Web Services (United States), IBM (United States), Oracle (United States), SAP (Germany), Microsoft (United States), Teradata (Germany), Software AG (Germany), Kognitio (United Kingdom), ENEA (Sweden) and Altibase (South Korea) etc.

3. What is Sql in In-Memory Database Market?
In-memory databases, in a contrast to databases that store data on disc or SSDs, are purpose-built databases that rely mostly on memory for data storage. By eliminating the need to access drives, in-memory data stores are designed to provide fast reaction times. In-memory databases risk losing data if a process or server fails since all data is stored and managed completely in the main memory. In-memory databases can persist data on discs by logging each activity or storing snapshots. In-Memory OLTP in SQL Server and SQL Database is the most advanced option for enhancing transaction processing, data intake, data load, and transient data scenarios.
Report Objectives / Segmentation Covered
By Deployment Mode
  • On-Premise
  • On-Demand

By End Users
  • Banks
  • Retail
  • Healthcare
  • E-Commerce
  • Aviation
  • Others

By Organization Size
  • Large Enterprises
  • Small and Medium Enterprises

By Processing Type
  • Online Analytical Processing (OLAP)
  • Online Transaction Processing (OLTP)

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Faster Data Processing
      • 3.2.2. Multi-User Concurrency
      • 3.2.3. A Huge Amount of Data Is Being Produced by Various Industries
    • 3.3. Market Challenges
      • 3.3.1. There is no Concept of HEAP
      • 3.3.2. In-Memory OLTP Does Not Have the Ability to Lock Records Like Regular SQL Server Queries Do, Save for an Application Lock
    • 3.4. Market Trends
      • 3.4.1. Rapid Development of SQL/NoSQL
      • 3.4.2. Rapid Prevalence of Hybrid Transactional and Analytical Processing (HTAP)
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Sql in In-Memory Database, by Deployment Mode, End Users, Organization Size, Processing Type and Region (value and price ) (2015-2020)
    • 5.1. Introduction
    • 5.2. Global Sql in In-Memory Database (Value)
      • 5.2.1. Global Sql in In-Memory Database by: Deployment Mode (Value)
        • 5.2.1.1. On-Premise
        • 5.2.1.2. On-Demand
      • 5.2.2. Global Sql in In-Memory Database by: End Users (Value)
        • 5.2.2.1. Banks
        • 5.2.2.2. Retail
        • 5.2.2.3. Healthcare
        • 5.2.2.4. E-Commerce
        • 5.2.2.5. Aviation
        • 5.2.2.6. Others
      • 5.2.3. Global Sql in In-Memory Database by: Organization Size (Value)
        • 5.2.3.1. Large Enterprises
        • 5.2.3.2. Small and Medium Enterprises
      • 5.2.4. Global Sql in In-Memory Database by: Processing Type (Value)
        • 5.2.4.1. Online Analytical Processing (OLAP)
        • 5.2.4.2. Online Transaction Processing (OLTP)
      • 5.2.5. Global Sql in In-Memory Database Region
        • 5.2.5.1. South America
          • 5.2.5.1.1. Brazil
          • 5.2.5.1.2. Argentina
          • 5.2.5.1.3. Rest of South America
        • 5.2.5.2. Asia Pacific
          • 5.2.5.2.1. China
          • 5.2.5.2.2. Japan
          • 5.2.5.2.3. India
          • 5.2.5.2.4. South Korea
          • 5.2.5.2.5. Taiwan
          • 5.2.5.2.6. Australia
          • 5.2.5.2.7. Rest of Asia-Pacific
        • 5.2.5.3. Europe
          • 5.2.5.3.1. Germany
          • 5.2.5.3.2. France
          • 5.2.5.3.3. Italy
          • 5.2.5.3.4. United Kingdom
          • 5.2.5.3.5. Netherlands
          • 5.2.5.3.6. Rest of Europe
        • 5.2.5.4. MEA
          • 5.2.5.4.1. Middle East
          • 5.2.5.4.2. Africa
        • 5.2.5.5. North America
          • 5.2.5.5.1. United States
          • 5.2.5.5.2. Canada
          • 5.2.5.5.3. Mexico
    • 5.3. Global Sql in In-Memory Database (Price)
  • 6. Sql in In-Memory Database: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2020)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Amazon Web Services (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. IBM (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Oracle (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. SAP (Germany)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Microsoft (United States)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Teradata (Germany)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Software AG (Germany)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Kognitio (United Kingdom)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. ENEA (Sweden)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Altibase (South Korea)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
  • 7. Global Sql in In-Memory Database Sale, by Deployment Mode, End Users, Organization Size, Processing Type and Region (value and price ) (2021-2026)
    • 7.1. Introduction
    • 7.2. Global Sql in In-Memory Database (Value)
      • 7.2.1. Global Sql in In-Memory Database by: Deployment Mode (Value)
        • 7.2.1.1. On-Premise
        • 7.2.1.2. On-Demand
      • 7.2.2. Global Sql in In-Memory Database by: End Users (Value)
        • 7.2.2.1. Banks
        • 7.2.2.2. Retail
        • 7.2.2.3. Healthcare
        • 7.2.2.4. E-Commerce
        • 7.2.2.5. Aviation
        • 7.2.2.6. Others
      • 7.2.3. Global Sql in In-Memory Database by: Organization Size (Value)
        • 7.2.3.1. Large Enterprises
        • 7.2.3.2. Small and Medium Enterprises
      • 7.2.4. Global Sql in In-Memory Database by: Processing Type (Value)
        • 7.2.4.1. Online Analytical Processing (OLAP)
        • 7.2.4.2. Online Transaction Processing (OLTP)
      • 7.2.5. Global Sql in In-Memory Database Region
        • 7.2.5.1. South America
          • 7.2.5.1.1. Brazil
          • 7.2.5.1.2. Argentina
          • 7.2.5.1.3. Rest of South America
        • 7.2.5.2. Asia Pacific
          • 7.2.5.2.1. China
          • 7.2.5.2.2. Japan
          • 7.2.5.2.3. India
          • 7.2.5.2.4. South Korea
          • 7.2.5.2.5. Taiwan
          • 7.2.5.2.6. Australia
          • 7.2.5.2.7. Rest of Asia-Pacific
        • 7.2.5.3. Europe
          • 7.2.5.3.1. Germany
          • 7.2.5.3.2. France
          • 7.2.5.3.3. Italy
          • 7.2.5.3.4. United Kingdom
          • 7.2.5.3.5. Netherlands
          • 7.2.5.3.6. Rest of Europe
        • 7.2.5.4. MEA
          • 7.2.5.4.1. Middle East
          • 7.2.5.4.2. Africa
        • 7.2.5.5. North America
          • 7.2.5.5.1. United States
          • 7.2.5.5.2. Canada
          • 7.2.5.5.3. Mexico
    • 7.3. Global Sql in In-Memory Database (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Sql in In-Memory Database: by Deployment Mode(USD Million)
  • Table 2. Sql in In-Memory Database On-Premise , by Region USD Million (2015-2020)
  • Table 3. Sql in In-Memory Database On-Demand , by Region USD Million (2015-2020)
  • Table 4. Sql in In-Memory Database: by End Users(USD Million)
  • Table 5. Sql in In-Memory Database Banks , by Region USD Million (2015-2020)
  • Table 6. Sql in In-Memory Database Retail , by Region USD Million (2015-2020)
  • Table 7. Sql in In-Memory Database Healthcare , by Region USD Million (2015-2020)
  • Table 8. Sql in In-Memory Database E-Commerce , by Region USD Million (2015-2020)
  • Table 9. Sql in In-Memory Database Aviation , by Region USD Million (2015-2020)
  • Table 10. Sql in In-Memory Database Others , by Region USD Million (2015-2020)
  • Table 11. Sql in In-Memory Database: by Organization Size(USD Million)
  • Table 12. Sql in In-Memory Database Large Enterprises , by Region USD Million (2015-2020)
  • Table 13. Sql in In-Memory Database Small and Medium Enterprises , by Region USD Million (2015-2020)
  • Table 14. Sql in In-Memory Database: by Processing Type(USD Million)
  • Table 15. Sql in In-Memory Database Online Analytical Processing (OLAP) , by Region USD Million (2015-2020)
  • Table 16. Sql in In-Memory Database Online Transaction Processing (OLTP) , by Region USD Million (2015-2020)
  • Table 17. South America Sql in In-Memory Database, by Country USD Million (2015-2020)
  • Table 18. South America Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 19. South America Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 20. South America Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 21. South America Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 22. Brazil Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 23. Brazil Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 24. Brazil Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 25. Brazil Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 26. Argentina Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 27. Argentina Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 28. Argentina Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 29. Argentina Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 30. Rest of South America Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 31. Rest of South America Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 32. Rest of South America Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 33. Rest of South America Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 34. Asia Pacific Sql in In-Memory Database, by Country USD Million (2015-2020)
  • Table 35. Asia Pacific Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 36. Asia Pacific Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 37. Asia Pacific Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 38. Asia Pacific Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 39. China Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 40. China Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 41. China Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 42. China Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 43. Japan Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 44. Japan Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 45. Japan Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 46. Japan Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 47. India Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 48. India Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 49. India Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 50. India Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 51. South Korea Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 52. South Korea Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 53. South Korea Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 54. South Korea Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 55. Taiwan Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 56. Taiwan Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 57. Taiwan Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 58. Taiwan Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 59. Australia Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 60. Australia Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 61. Australia Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 62. Australia Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 63. Rest of Asia-Pacific Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 64. Rest of Asia-Pacific Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 65. Rest of Asia-Pacific Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 66. Rest of Asia-Pacific Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 67. Europe Sql in In-Memory Database, by Country USD Million (2015-2020)
  • Table 68. Europe Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 69. Europe Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 70. Europe Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 71. Europe Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 72. Germany Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 73. Germany Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 74. Germany Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 75. Germany Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 76. France Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 77. France Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 78. France Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 79. France Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 80. Italy Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 81. Italy Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 82. Italy Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 83. Italy Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 84. United Kingdom Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 85. United Kingdom Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 86. United Kingdom Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 87. United Kingdom Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 88. Netherlands Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 89. Netherlands Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 90. Netherlands Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 91. Netherlands Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 92. Rest of Europe Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 93. Rest of Europe Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 94. Rest of Europe Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 95. Rest of Europe Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 96. MEA Sql in In-Memory Database, by Country USD Million (2015-2020)
  • Table 97. MEA Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 98. MEA Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 99. MEA Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 100. MEA Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 101. Middle East Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 102. Middle East Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 103. Middle East Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 104. Middle East Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 105. Africa Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 106. Africa Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 107. Africa Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 108. Africa Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 109. North America Sql in In-Memory Database, by Country USD Million (2015-2020)
  • Table 110. North America Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 111. North America Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 112. North America Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 113. North America Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 114. United States Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 115. United States Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 116. United States Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 117. United States Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 118. Canada Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 119. Canada Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 120. Canada Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 121. Canada Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 122. Mexico Sql in In-Memory Database, by Deployment Mode USD Million (2015-2020)
  • Table 123. Mexico Sql in In-Memory Database, by End Users USD Million (2015-2020)
  • Table 124. Mexico Sql in In-Memory Database, by Organization Size USD Million (2015-2020)
  • Table 125. Mexico Sql in In-Memory Database, by Processing Type USD Million (2015-2020)
  • Table 126. Company Basic Information, Sales Area and Its Competitors
  • Table 127. Company Basic Information, Sales Area and Its Competitors
  • Table 128. Company Basic Information, Sales Area and Its Competitors
  • Table 129. Company Basic Information, Sales Area and Its Competitors
  • Table 130. Company Basic Information, Sales Area and Its Competitors
  • Table 131. Company Basic Information, Sales Area and Its Competitors
  • Table 132. Company Basic Information, Sales Area and Its Competitors
  • Table 133. Company Basic Information, Sales Area and Its Competitors
  • Table 134. Company Basic Information, Sales Area and Its Competitors
  • Table 135. Company Basic Information, Sales Area and Its Competitors
  • Table 136. Sql in In-Memory Database: by Deployment Mode(USD Million)
  • Table 137. Sql in In-Memory Database On-Premise , by Region USD Million (2021-2026)
  • Table 138. Sql in In-Memory Database On-Demand , by Region USD Million (2021-2026)
  • Table 139. Sql in In-Memory Database: by End Users(USD Million)
  • Table 140. Sql in In-Memory Database Banks , by Region USD Million (2021-2026)
  • Table 141. Sql in In-Memory Database Retail , by Region USD Million (2021-2026)
  • Table 142. Sql in In-Memory Database Healthcare , by Region USD Million (2021-2026)
  • Table 143. Sql in In-Memory Database E-Commerce , by Region USD Million (2021-2026)
  • Table 144. Sql in In-Memory Database Aviation , by Region USD Million (2021-2026)
  • Table 145. Sql in In-Memory Database Others , by Region USD Million (2021-2026)
  • Table 146. Sql in In-Memory Database: by Organization Size(USD Million)
  • Table 147. Sql in In-Memory Database Large Enterprises , by Region USD Million (2021-2026)
  • Table 148. Sql in In-Memory Database Small and Medium Enterprises , by Region USD Million (2021-2026)
  • Table 149. Sql in In-Memory Database: by Processing Type(USD Million)
  • Table 150. Sql in In-Memory Database Online Analytical Processing (OLAP) , by Region USD Million (2021-2026)
  • Table 151. Sql in In-Memory Database Online Transaction Processing (OLTP) , by Region USD Million (2021-2026)
  • Table 152. South America Sql in In-Memory Database, by Country USD Million (2021-2026)
  • Table 153. South America Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 154. South America Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 155. South America Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 156. South America Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 157. Brazil Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 158. Brazil Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 159. Brazil Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 160. Brazil Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 161. Argentina Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 162. Argentina Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 163. Argentina Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 164. Argentina Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 165. Rest of South America Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 166. Rest of South America Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 167. Rest of South America Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 168. Rest of South America Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 169. Asia Pacific Sql in In-Memory Database, by Country USD Million (2021-2026)
  • Table 170. Asia Pacific Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 171. Asia Pacific Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 172. Asia Pacific Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 173. Asia Pacific Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 174. China Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 175. China Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 176. China Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 177. China Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 178. Japan Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 179. Japan Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 180. Japan Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 181. Japan Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 182. India Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 183. India Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 184. India Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 185. India Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 186. South Korea Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 187. South Korea Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 188. South Korea Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 189. South Korea Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 190. Taiwan Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 191. Taiwan Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 192. Taiwan Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 193. Taiwan Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 194. Australia Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 195. Australia Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 196. Australia Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 197. Australia Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 198. Rest of Asia-Pacific Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 199. Rest of Asia-Pacific Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 200. Rest of Asia-Pacific Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 201. Rest of Asia-Pacific Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 202. Europe Sql in In-Memory Database, by Country USD Million (2021-2026)
  • Table 203. Europe Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 204. Europe Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 205. Europe Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 206. Europe Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 207. Germany Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 208. Germany Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 209. Germany Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 210. Germany Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 211. France Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 212. France Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 213. France Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 214. France Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 215. Italy Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 216. Italy Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 217. Italy Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 218. Italy Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 219. United Kingdom Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 220. United Kingdom Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 221. United Kingdom Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 222. United Kingdom Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 223. Netherlands Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 224. Netherlands Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 225. Netherlands Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 226. Netherlands Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 227. Rest of Europe Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 228. Rest of Europe Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 229. Rest of Europe Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 230. Rest of Europe Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 231. MEA Sql in In-Memory Database, by Country USD Million (2021-2026)
  • Table 232. MEA Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 233. MEA Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 234. MEA Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 235. MEA Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 236. Middle East Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 237. Middle East Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 238. Middle East Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 239. Middle East Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 240. Africa Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 241. Africa Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 242. Africa Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 243. Africa Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 244. North America Sql in In-Memory Database, by Country USD Million (2021-2026)
  • Table 245. North America Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 246. North America Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 247. North America Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 248. North America Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 249. United States Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 250. United States Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 251. United States Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 252. United States Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 253. Canada Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 254. Canada Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 255. Canada Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 256. Canada Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 257. Mexico Sql in In-Memory Database, by Deployment Mode USD Million (2021-2026)
  • Table 258. Mexico Sql in In-Memory Database, by End Users USD Million (2021-2026)
  • Table 259. Mexico Sql in In-Memory Database, by Organization Size USD Million (2021-2026)
  • Table 260. Mexico Sql in In-Memory Database, by Processing Type USD Million (2021-2026)
  • Table 261. Research Programs/Design for This Report
  • Table 262. Key Data Information from Secondary Sources
  • Table 263. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Sql in In-Memory Database: by Deployment Mode USD Million (2015-2020)
  • Figure 5. Global Sql in In-Memory Database: by End Users USD Million (2015-2020)
  • Figure 6. Global Sql in In-Memory Database: by Organization Size USD Million (2015-2020)
  • Figure 7. Global Sql in In-Memory Database: by Processing Type USD Million (2015-2020)
  • Figure 8. South America Sql in In-Memory Database Share (%), by Country
  • Figure 9. Asia Pacific Sql in In-Memory Database Share (%), by Country
  • Figure 10. Europe Sql in In-Memory Database Share (%), by Country
  • Figure 11. MEA Sql in In-Memory Database Share (%), by Country
  • Figure 12. North America Sql in In-Memory Database Share (%), by Country
  • Figure 13. Global Sql in In-Memory Database share by Players 2020 (%)
  • Figure 14. Global Sql in In-Memory Database share by Players (Top 3) 2020(%)
  • Figure 15. Global Sql in In-Memory Database share by Players (Top 5) 2020(%)
  • Figure 16. BCG Matrix for key Companies
  • Figure 17. Amazon Web Services (United States) Revenue, Net Income and Gross profit
  • Figure 18. Amazon Web Services (United States) Revenue: by Geography 2020
  • Figure 19. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 20. IBM (United States) Revenue: by Geography 2020
  • Figure 21. Oracle (United States) Revenue, Net Income and Gross profit
  • Figure 22. Oracle (United States) Revenue: by Geography 2020
  • Figure 23. SAP (Germany) Revenue, Net Income and Gross profit
  • Figure 24. SAP (Germany) Revenue: by Geography 2020
  • Figure 25. Microsoft (United States) Revenue, Net Income and Gross profit
  • Figure 26. Microsoft (United States) Revenue: by Geography 2020
  • Figure 27. Teradata (Germany) Revenue, Net Income and Gross profit
  • Figure 28. Teradata (Germany) Revenue: by Geography 2020
  • Figure 29. Software AG (Germany) Revenue, Net Income and Gross profit
  • Figure 30. Software AG (Germany) Revenue: by Geography 2020
  • Figure 31. Kognitio (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 32. Kognitio (United Kingdom) Revenue: by Geography 2020
  • Figure 33. ENEA (Sweden) Revenue, Net Income and Gross profit
  • Figure 34. ENEA (Sweden) Revenue: by Geography 2020
  • Figure 35. Altibase (South Korea) Revenue, Net Income and Gross profit
  • Figure 36. Altibase (South Korea) Revenue: by Geography 2020
  • Figure 37. Global Sql in In-Memory Database: by Deployment Mode USD Million (2021-2026)
  • Figure 38. Global Sql in In-Memory Database: by End Users USD Million (2021-2026)
  • Figure 39. Global Sql in In-Memory Database: by Organization Size USD Million (2021-2026)
  • Figure 40. Global Sql in In-Memory Database: by Processing Type USD Million (2021-2026)
  • Figure 41. South America Sql in In-Memory Database Share (%), by Country
  • Figure 42. Asia Pacific Sql in In-Memory Database Share (%), by Country
  • Figure 43. Europe Sql in In-Memory Database Share (%), by Country
  • Figure 44. MEA Sql in In-Memory Database Share (%), by Country
  • Figure 45. North America Sql in In-Memory Database Share (%), by Country
Some of the key companies/manufacturers profiled in the report
  • Amazon Web Services (United States)
  • IBM (United States)
  • Oracle (United States)
  • SAP (Germany)
  • Microsoft (United States)
  • Teradata (Germany)
  • Software AG (Germany)
  • Kognitio (United Kingdom)
  • ENEA (Sweden)
  • Altibase (South Korea)
Additional players considered in the study are as follows:
Redis Labs (United States) , Splice Machine (United States) , Hazelcast (United States)
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