Relational In-Memory Database Market, Global Outlook and Forecast 2023-2035
An Relational in-memory database (IMDB) is a database management system that primarily depends on main memory for storing computer data. IMDBs are quicker than disk-optimized databases because they carry out fewer CPU instructions, and their internal optimization algorithms are much simpler. IMDB eradicates disk access by saving and manipulating data in the main memory. An IMDB commonly includes direct data manipulation and a dedicated memory-based architecture.
This report aims to provide a comprehensive presentation of the global market for Relational In-Memory Database, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Relational In-Memory Database. This report contains market size and forecasts of Relational In-Memory Database in global, including the following market information:
Global Relational In-Memory Database Market Revenue, 2018-2023, 20242035, ($ millions)
Global top five companies in 2022 (%)
The global Relational In-Memory Database market was valued at US$ million in 2022 and is projected to reach US$ million by 2029, at a CAGR of % during the forecast period. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.
The U.S. Market is Estimated at $ Million in 2022, While China is to reach $ Million.
Main Memory Database (MMDB) Segment to Reach $ Million by 2029, with a % CAGR in next six years.
The global key manufacturers of Relational In-Memory Database include Microsoft, IBM, Oracle, SAP, Teradata, Amazon, Tableau, Kognitio and Volt, etc. in 2022, the global top five players have a share approximately % in terms of revenue.
We surveyed the Relational In-Memory Database companies, and industry experts on this industry, involving the revenue, demand, product type, recent developments and plans, industry trends, drivers, challenges, obstacles, and potential risks.
Total Market by Segment:
Global Relational In-Memory Database Market, by Type, 2018-2023, 20242035 ($ millions)
Global Relational In-Memory Database Market Segment Percentages, by Type, 2022 (%)
Main Memory Database (MMDB)
Real-time Database (RTDB)
Global Relational In-Memory Database Market, by Application, 2018-2023, 20242035 ($ millions)
Global Relational In-Memory Database Market Segment Percentages, by Application, 2022 (%)
Transaction
Reporting
Analytics
Global Relational In-Memory Database Market, By Region and Country, 2018-2023, 20242035 ($ Millions)
Global Relational In-Memory Database Market Segment Percentages, By Region and Country, 2022 (%)
North America
US
Canada
Mexico
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Benelux
Rest of Europe
Asia
China
Japan
South Korea
Southeast Asia
India
Rest of Asia
South America
Brazil
Argentina
Rest of South America
Middle East & Africa
Turkey
Israel
Saudi Arabia
UAE
Rest of Middle East & Africa
Competitor Analysis
The report also provides analysis of leading market participants including:
Key companies Relational In-Memory Database revenues in global market, 2018-2023 (estimated), ($ millions)
Key companies Relational In-Memory Database revenues share in global market, 2022 (%)
Further, the report presents profiles of competitors in the market, key players include:
Microsoft
IBM
Oracle
SAP
Teradata
Amazon
Tableau
Kognitio
Volt
DataStax
ENEA
McObject
Altibase
Outline of Major Chapters:
Chapter 1: Introduces the definition of Relational In-Memory Database, market overview.
Chapter 2: Global Relational In-Memory Database market size in revenue.
Chapter 3: Detailed analysis of Relational In-Memory Database company competitive landscape, revenue and market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6: Sales of Relational In-Memory Database in regional level and country level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space of each country in the world.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 8: The main points and conclusions of the report.
