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In-memory OLAP is the method by which analytical data is loaded into memory for live calculations and querying. Because the data is loaded into memory, running queries (or, in OLAP terms, slicing and dicing), can be faster then with traditional relational on-line analytical processing (ROLAP), multidimensional OLAP (MOLAP) and hybrid systems. Since the data resides in the RAM, the system does not need to reach out to a database or a physical file which may further entail additional network operations and disk read/write operations. Furthermore, traditional cubes store pre-calculated data and results which can then be queried. This limits the number of pre-calculated combinations. With RAM-based analytics, these calculations can sometimes be just as quickly generated on the fly.
Scope of the Report:
This report studies the In-memory OLAP Database market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the In-memory OLAP Database market by product type and applications/end industries.
A number of established and new vendors have come out with in-memory OLAP technologies. While the concept is at least a decade old, it is gaining more acceptance due to cheaper Random Access Memory (RAM) and faster CPU speeds.
The global In-memory OLAP Database market is valued at xx million USD in 2017 and is expected to reach xx million USD by the end of 2023, growing at a CAGR of xx% between 2017 and 2023.
The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions.
North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of In-memory OLAP Database.
Europe also play important roles in global market, with market size of xx million USD in 2017 and will be xx million USD in 2023, with a CAGR of xx%.
Market Segment by Companies, this report covers
Altibase
IBM
Microsoft
Oracle
SAP SE
Exasol
Jedox
Kognitio
Mcobject
MemSQL
MicroStrategy
SAS Institute
Teradata
Terracotta
VoltDB
Market Segment by Regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia and Italy)
Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
South America (Brazil, Argentina, Colombia)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
Market Segment by Type, covers
Transaction
Reporting
Analytics
Market Segment by Applications, can be divided into
BFSI
Government and Defense
Healthcare and Life Sciences
Retail and Consumer Goods
Transportation and Logistics
IT and Telecommunication
Manufacturing
Energy and Utility
The base year for the study has been considered 2019, historic year 2014 and 2018, the forecast period considered is from 2020 to 2027. The regions analyzed for the market include North America, Europe, South America, Asia Pacific, and Middle East and Africa. These regions are further analyzed at the country-level. The study also includes attractiveness analysis of type, application and regions which are benchmarked based on their market size, growth rate and attractiveness in terms of present and future opportunity for understanding the future growth of the market.
Market is segmented on the basis:
The report offers in-depth analysis of driving factors, opportunities, restraints, and challenges for gaining the key insight of the market. The report emphasizes on all the key trends that play a vital role in the enlargement of the market from 2019 to 2026.
The report provides company profile of the key players operating in the market and a comparative analysis based on their business overviews industry offering, segment market share, regional presence, business strategies, innovations, mergers & acquisitions, recent developments, joint venture, collaborations, partnerships, SWOT analysis, and key financial information.
Table of Contents
1 In-memory OLAP Database Market Overview
1.1 Product Overview and Scope of In-memory OLAP Database
1.2 Classification of In-memory OLAP Database by Types
1.2.1 Global In-memory OLAP Database Revenue Comparison by Types (2017-2023)
1.2.2 Global In-memory OLAP Database Revenue Market Share by Types in 2017
1.2.3 Transaction
1.2.4 Reporting
1.2.5 Analytics
1.3 Global In-memory OLAP Database Market by Application
1.3.1 Global In-memory OLAP Database Market Size and Market Share Comparison by Applications (2013-2023)
1.3.2 BFSI
1.3.3 Government and Defense
1.3.4 Healthcare and Life Sciences
1.3.5 Retail and Consumer Goods
1.3.6 Transportation and Logistics
1.3.7 IT and Telecommunication
1.3.8 Manufacturing
1.3.9 Energy and Utility
1.4 Global In-memory OLAP Database Market by Regions
1.4.1 Global In-memory OLAP Database Market Size (Million USD) Comparison by Regions (2013-2023)
1.4.1 North America (USA, Canada and Mexico) In-memory OLAP Database Status and Prospect (2013-2023)
1.4.2 Europe (Germany, France, UK, Russia and Italy) In-memory OLAP Database Status and Prospect (2013-2023)
1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia) In-memory OLAP Database Status and Prospect (2013-2023)
1.4.4 South America (Brazil, Argentina, Colombia) In-memory OLAP Database Status and Prospect (2013-2023)
1.4.5 Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) In-memory OLAP Database Status and Prospect (2013-2023)
1.5 Global Market Size of In-memory OLAP Database (2013-2023)
2 Manufacturers Profiles
2.1 Altibase
2.1.1 Business Overview
2.1.2 In-memory OLAP Database Type and Applications
2.1.2.1 Product A
2.1.2.2 Product B
2.1.3 Altibase In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.2 IBM
2.2.1 Business Overview
2.2.2 In-memory OLAP Database Type and Applications
2.2.2.1 Product A
2.2.2.2 Product B
2.2.3 IBM In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.3 Microsoft
2.3.1 Business Overview
2.3.2 In-memory OLAP Database Type and Applications
2.3.2.1 Product A
2.3.2.2 Product B
2.3.3 Microsoft In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.4 Oracle
2.4.1 Business Overview
2.4.2 In-memory OLAP Database Type and Applications
2.4.2.1 Product A
2.4.2.2 Product B
2.4.3 Oracle In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.5 SAP SE
2.5.1 Business Overview
2.5.2 In-memory OLAP Database Type and Applications
2.5.2.1 Product A
2.5.2.2 Product B
2.5.3 SAP SE In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.6 Exasol
2.6.1 Business Overview
2.6.2 In-memory OLAP Database Type and Applications
2.6.2.1 Product A
2.6.2.2 Product B
2.6.3 Exasol In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.7 Jedox
2.7.1 Business Overview
2.7.2 In-memory OLAP Database Type and Applications
2.7.2.1 Product A
2.7.2.2 Product B
2.7.3 Jedox In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.8 Kognitio
2.8.1 Business Overview
2.8.2 In-memory OLAP Database Type and Applications
2.8.2.1 Product A
2.8.2.2 Product B
2.8.3 Kognitio In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.9 Mcobject
2.9.1 Business Overview
2.9.2 In-memory OLAP Database Type and Applications
2.9.2.1 Product A
2.9.2.2 Product B
2.9.3 Mcobject In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.10 MemSQL
2.10.1 Business Overview
2.10.2 In-memory OLAP Database Type and Applications
2.10.2.1 Product A
2.10.2.2 Product B
2.10.3 MemSQL In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.11 MicroStrategy
2.11.1 Business Overview
2.11.2 In-memory OLAP Database Type and Applications
2.11.2.1 Product A
2.11.2.2 Product B
2.11.3 MicroStrategy In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.12 SAS Institute
2.12.1 Business Overview
2.12.2 In-memory OLAP Database Type and Applications
2.12.2.1 Product A
2.12.2.2 Product B
2.12.3 SAS Institute In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.13 Teradata
2.13.1 Business Overview
2.13.2 In-memory OLAP Database Type and Applications
2.13.2.1 Product A
2.13.2.2 Product B
2.13.3 Teradata In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.14 Terracotta
2.14.1 Business Overview
2.14.2 In-memory OLAP Database Type and Applications
2.14.2.1 Product A
2.14.2.2 Product B
2.14.3 Terracotta In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
2.15 VoltDB
2.15.1 Business Overview
2.15.2 In-memory OLAP Database Type and Applications
2.15.2.1 Product A
2.15.2.2 Product B
2.15.3 VoltDB In-memory OLAP Database Revenue, Gross Margin and Market Share (2016-2017)
3 Global In-memory OLAP Database Market Competition, by Players
3.1 Global In-memory OLAP Database Revenue and Share by Players (2013-2018)
3.2 Market Concentration Rate
3.2.1 Top 5 In-memory OLAP Database Players Market Share
3.2.2 Top 10 In-memory OLAP Database Players Market Share
3.3 Market Competition Trend
4 Global In-memory OLAP Database Market Size by Regions
4.1 Global In-memory OLAP Database Revenue and Market Share by Regions
4.2 North America In-memory OLAP Database Revenue and Growth Rate (2013-2018)
4.3 Europe In-memory OLAP Database Revenue and Growth Rate (2013-2018)
4.4 Asia-Pacific In-memory OLAP Database Revenue and Growth Rate (2013-2018)
4.5 South America In-memory OLAP Database Revenue and Growth Rate (2013-2018)
4.6 Middle East and Africa In-memory OLAP Database Revenue and Growth Rate (2013-2018)
5 North America In-memory OLAP Database Revenue by Countries
5.1 North America In-memory OLAP Database Revenue by Countries (2013-2018)
5.2 USA In-memory OLAP Database Revenue and Growth Rate (2013-2018)
5.3 Canada In-memory OLAP Database Revenue and Growth Rate (2013-2018)
5.4 Mexico In-memory OLAP Database Revenue and Growth Rate (2013-2018)
6 Europe In-memory OLAP Database Revenue by Countries
6.1 Europe In-memory OLAP Database Revenue by Countries (2013-2018)
6.2 Germany In-memory OLAP Database Revenue and Growth Rate (2013-2018)
6.3 UK In-memory OLAP Database Revenue and Growth Rate (2013-2018)
6.4 France In-memory OLAP Database Revenue and Growth Rate (2013-2018)
6.5 Russia In-memory OLAP Database Revenue and Growth Rate (2013-2018)
6.6 Italy In-memory OLAP Database Revenue and Growth Rate (2013-2018)
7 Asia-Pacific In-memory OLAP Database Revenue by Countries
7.1 Asia-Pacific In-memory OLAP Database Revenue by Countries (2013-2018)
7.2 China In-memory OLAP Database Revenue and Growth Rate (2013-2018)
7.3 Japan In-memory OLAP Database Revenue and Growth Rate (2013-2018)
7.4 Korea In-memory OLAP Database Revenue and Growth Rate (2013-2018)
7.5 India In-memory OLAP Database Revenue and Growth Rate (2013-2018)
7.6 Southeast Asia In-memory OLAP Database Revenue and Growth Rate (2013-2018)
8 South America In-memory OLAP Database Revenue by Countries
8.1 South America In-memory OLAP Database Revenue by Countries (2013-2018)
8.2 Brazil In-memory OLAP Database Revenue and Growth Rate (2013-2018)
8.3 Argentina In-memory OLAP Database Revenue and Growth Rate (2013-2018)
8.4 Colombia In-memory OLAP Database Revenue and Growth Rate (2013-2018)
9 Middle East and Africa Revenue In-memory OLAP Database by Countries
9.1 Middle East and Africa In-memory OLAP Database Revenue by Countries (2013-2018)
9.2 Saudi Arabia In-memory OLAP Database Revenue and Growth Rate (2013-2018)
9.3 UAE In-memory OLAP Database Revenue and Growth Rate (2013-2018)
9.4 Egypt In-memory OLAP Database Revenue and Growth Rate (2013-2018)
9.5 Nigeria In-memory OLAP Database Revenue and Growth Rate (2013-2018)
9.6 South Africa In-memory OLAP Database Revenue and Growth Rate (2013-2018)
10 Global In-memory OLAP Database Market Segment by Type
10.1 Global In-memory OLAP Database Revenue and Market Share by Type (2013-2018)
10.2 Global In-memory OLAP Database Market Forecast by Type (2018-2023)
10.3 Transaction Revenue Growth Rate (2013-2023)
10.4 Reporting Revenue Growth Rate (2013-2023)
10.5 Analytics Revenue Growth Rate (2013-2023)
11 Global In-memory OLAP Database Market Segment by Application
11.1 Global In-memory OLAP Database Revenue Market Share by Application (2013-2018)
11.2 In-memory OLAP Database Market Forecast by Application (2018-2023)
11.3 BFSI Revenue Growth (2013-2018)
11.4 Government and Defense Revenue Growth (2013-2018)
11.5 Healthcare and Life Sciences Revenue Growth (2013-2018)
11.6 Retail and Consumer Goods Revenue Growth (2013-2018)
11.7 Transportation and Logistics Revenue Growth (2013-2018)
11.8 IT and Telecommunication Revenue Growth (2013-2018)
11.9 Manufacturing Revenue Growth (2013-2018)
11.10 Energy and Utility Revenue Growth (2013-2018)
12 Global In-memory OLAP Database Market Size Forecast (2018-2023)
12.1 Global In-memory OLAP Database Market Size Forecast (2018-2023)
12.2 Global In-memory OLAP Database Market Forecast by Regions (2018-2023)
12.3 North America In-memory OLAP Database Revenue Market Forecast (2018-2023)
12.4 Europe In-memory OLAP Database Revenue Market Forecast (2018-2023)
12.5 Asia-Pacific In-memory OLAP Database Revenue Market Forecast (2018-2023)
12.6 South America In-memory OLAP Database Revenue Market Forecast (2018-2023)
12.7 Middle East and Africa In-memory OLAP Database Revenue Market Forecast (2018-2023)
13 Research Findings and Conclusion
14 Appendix
14.1 Methodology
14.2 Data Source
List of Tables and Figures
Figure In-memory OLAP Database Picture
Table Product Specifications of In-memory OLAP Database
Table Global In-memory OLAP Database and Revenue (Million USD) Market Split b
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