Market Overview:
The global relational in-memory database market is expected to grow at a CAGR of xx% during the forecast period from 2018 to 2030. The growth of the market can be attributed to the increasing demand for real-time and transactional applications, rising trend of big data and analytics, and growing need for faster decision making. The MMDB segment is expected to hold the largest share of the global relational in-memory database market during the forecast period. This can be attributed to its ability to handle large scale data processing requirements and provide fast performance. The RTDB segment is projected to grow at a higher CAGR than MMDB during the forecast period owing to its ability manage high throughputs and low response times required by online transaction processing (OLTP) systems. In terms of application, transaction processing is expected hold majority share of global relational in-memory database market during 2018–2030 followed by reporting & analytics segments respectively. Transaction processing requires high performance with low latency which can be achieved through deployment of RTDB solutions over MMDB solutions.
Product Definition:
A relational in-memory database is a type of database management system that stores data in memory. This type of database is often used for high-performance applications, such as online transaction processing systems or real-time analytics.
Main Memory Database (MMDB):
The global Main Memory Database (MMDB) market size was valued at USD 0.00 billion in 2016 and is expected to grow at a CAGR of XX% over the forecast period.
Real-time Database (RTDB):
Real-time database (RTDB) is a type of in-memory database that provides real-time data storage. RTDBs are used to store the current state of an application and provide updates as and when required. The key benefit offered by RTDBS is that it reduces the time taken to get updated information from Database Server compared to normal databases which can be accessed through JDBC drivers.
Application Insights:
The transaction application segment accounted for the largest market share in 2017 and is expected to continue its dominance over the forecast period. The growth of this segment can be attributed to increasing demand from banking, financial services, and insurance (BFSI) sector for real-time analytics. In addition, growing adoption of these solutions by retailers for inventory management is expected to drive the global in-memory database market over the forecast period.
The reporting application segment is anticipated register a significant CAGR during the study period owing to increased demand from various industries such as healthcare, retail, manufacturing etc. For instance; pharmaceutical companies are extensively using reporting applications such as Microsoft SQL Server Reporting Services (SSRS) or Report Builder 2.0 for generating operational reports which are used by managers at different levels of an organization to make informed decisions about business operations and identify trends that would otherwise go unnoticed. Such factors are projected to fuel industry growth during future years (2030).
Regional Analysis:
North America dominated the global market in 2017. The growth can be attributed to the presence of major players, such as Oracle Corporation; Microsoft Corporation; IBM Corporation; and Google Inc., in this region. Moreover, increasing demand for on-demand computing along with rapid technological advancements is expected to drive regional growth over the forecast period.
The Asia Pacific regional market is anticipated to witness significant growth over the forecast period owing to increasing investments by prominent players in this region for developing new products and applications based on RLI-memory technology. Furthermore, growing adoption of cloud services among enterprises coupled with rising need for real-time data processing capabilities are some factors driving regional demand during the forecast period. Additionally, government initiatives encouraging digitalization are also expected to contribute toward industry development within APAC region over next few years (For eample: Digital India Program).
Growth Factors:
- Increasing demand for big data and analytics: The relational in-memory database market is expected to grow due to the increasing demand for big data and analytics. Organizations are looking for ways to manage and analyze large amounts of data in order to make better decisions. In-memory databases can help organizations achieve this by allowing them to access data quickly and easily.
- Growing popularity of cloud computing: Cloud computing is becoming increasingly popular, as it allows organizations to access IT resources on an as-needed basis. In-memory databases can be hosted in the cloud, which makes them a good fit for organizations that want the flexibility and scalability that cloud computing provides.
- Advances in technology: Technology advances are making it possible for in-memory databases to handle larger amounts of data more efficiently than ever before. This is helping fuel the growth of the relational in-memory database market.
Scope Of The Report
Report Attributes
Report Details
Report Title
Relational In-Memory Database Market Research Report
By Type
Main Memory Database (MMDB), Real-time Database (RTDB)
By Application
Transaction, Reporting, Analytics
By Companies
Microsoft, IBM, Oracle, SAP, Teradata, Amazon, Tableau, Kognitio, Volt, DataStax, ENEA, McObject, Altibase
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
133
Number of Tables & Figures
94
Customization Available
Yes, the report can be customized as per your need.
Global Relational In-Memory Database Market Report Segments:
The global Relational In-Memory Database market is segmented on the basis of:
Types
Main Memory Database (MMDB), Real-time Database (RTDB)
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Transaction, Reporting, Analytics
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Microsoft
- IBM
- Oracle
- SAP
- Teradata
- Amazon
- Tableau
- Kognitio
- Volt
- DataStax
- ENEA
- McObject
- Altibase
Highlights of The Relational In-Memory Database Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Main Memory Database (MMDB)
- Real-time Database (RTDB)
- By Application:
- Transaction
- Reporting
- Analytics
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Relational In-Memory Database Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
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8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Relational in-memory database is a database management system that stores data in memory instead of on disk. This allows for faster access to the data, which can be important when the database is used for applications that need to respond quickly to user input.
Some of the key players operating in the relational in-memory database market are Microsoft, IBM, Oracle, SAP, Teradata, Amazon, Tableau, Kognitio, Volt, DataStax, ENEA, McObject, Altibase.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Relational In-Memory Database Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Relational In-Memory Database Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Relational In-Memory Database Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Relational In-Memory Database Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Relational In-Memory Database Market Size & Forecast, 2018-2028
4.5.1 Relational In-Memory Database Market Size and Y-o-Y Growth
4.5.2 Relational In-Memory Database Market Absolute $ Opportunity
Chapter 5 Global Relational In-Memory Database Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Relational In-Memory Database Market Size Forecast by Type
5.2.1 Main Memory Database (MMDB)
5.2.2 Real-time Database (RTDB)
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Relational In-Memory Database Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Relational In-Memory Database Market Size Forecast by Applications
6.2.1 Transaction
6.2.2 Reporting
6.2.3 Analytics
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Relational In-Memory Database Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Relational In-Memory Database Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Relational In-Memory Database Analysis and Forecast
9.1 Introduction
9.2 North America Relational In-Memory Database Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Relational In-Memory Database Market Size Forecast by Type
9.6.1 Main Memory Database (MMDB)
9.6.2 Real-time Database (RTDB)
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Relational In-Memory Database Market Size Forecast by Applications
9.10.1 Transaction
9.10.2 Reporting
9.10.3 Analytics
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Relational In-Memory Database Analysis and Forecast
10.1 Introduction
10.2 Europe Relational In-Memory Database Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Relational In-Memory Database Market Size Forecast by Type
10.6.1 Main Memory Database (MMDB)
10.6.2 Real-time Database (RTDB)
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Relational In-Memory Database Market Size Forecast by Applications
10.10.1 Transaction
10.10.2 Reporting
10.10.3 Analytics
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Relational In-Memory Database Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Relational In-Memory Database Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Relational In-Memory Database Market Size Forecast by Type
11.6.1 Main Memory Database (MMDB)
11.6.2 Real-time Database (RTDB)
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Relational In-Memory Database Market Size Forecast by Applications
11.10.1 Transaction
11.10.2 Reporting
11.10.3 Analytics
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Relational In-Memory Database Analysis and Forecast
12.1 Introduction
12.2 Latin America Relational In-Memory Database Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Relational In-Memory Database Market Size Forecast by Type
12.6.1 Main Memory Database (MMDB)
12.6.2 Real-time Database (RTDB)
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Relational In-Memory Database Market Size Forecast by Applications
12.10.1 Transaction
12.10.2 Reporting
12.10.3 Analytics
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Relational In-Memory Database Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Relational In-Memory Database Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Relational In-Memory Database Market Size Forecast by Type
13.6.1 Main Memory Database (MMDB)
13.6.2 Real-time Database (RTDB)
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Relational In-Memory Database Market Size Forecast by Applications
13.10.1 Transaction
13.10.2 Reporting
13.10.3 Analytics
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Relational In-Memory Database Market: Competitive Dashboard
14.2 Global Relational In-Memory Database Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Microsoft
14.3.2 IBM
14.3.3 Oracle
14.3.4 SAP
14.3.5 Teradata
14.3.6 Amazon
14.3.7 Tableau
14.3.8 Kognitio
14.3.9 Volt
14.3.10 DataStax
14.3.11 ENEA
14.3.12 McObject
14.3.13 Altibase
