Global In-memory OLAP Database Market Application, Revenue Status, Leading Player, Demand, Growth, Future Opportunity & Forecast to 2025

Market Research Hub (MRH) has recently broadcasted a new study to its broad research portfolio, which is titled as “Global In-memory OLAP Database Market Size, Status and Forecast 2025” provides an in-depth analysis of the In-memory OLAP Database with the forecast of market size and growth. The analysis includes addressable market, market by volume, and market share by business type and by segment (external and in-house).The research study examines the In-memory OLAP Database on the basis of a number of criteria, such as the product type, application, and its geographical presence.

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This report studies the global In-memory OLAP Database market size, industry status and forecast, competition landscape and growth opportunity. This research report categorizes the global In-memory OLAP Database market by companies, region, type and end-use industry.

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.
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.
In 2017, the global In-memory OLAP Database market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2018-2025.

This report focuses on the global top players, covered
Altibase
IBM
Microsoft
Oracle
SAP SE
Exasol
Jedox
Kognitio
Mcobject
MemSQL
MicroStrategy
SAS Institute
Teradata
Terracotta
VoltDB

Market segment by Regions/Countries, this report covers
United States
Europe
China
Japan
Southeast Asia
India

Market segment by Type, the product can be split into
Transaction
Reporting
Analytics

Market segment by Application, split into
BFSI
Government and Defense
Healthcare and Life Sciences
Retail and Consumer Goods
Transportation and Logistics
IT and Telecommunication
Manufacturing
Energy and Utility

Browse Full Report with Table of Content: https://www.marketresearchhub.com/report/global-in-memory-olap-database-market-size-status-and-forecast-2025-report.html

Table of Content:

Global In-memory OLAP Database Market Size, Status and Forecast 2025
1 Industry Overview of In-memory OLAP Database
1.1 In-memory OLAP Database Market Overview
1.1.1 In-memory OLAP Database Product Scope
1.1.2 Market Status and Outlook
1.2 Global In-memory OLAP Database Market Size and Analysis by Regions (2013-2018)
1.2.1 United States
1.2.2 Europe
1.2.3 China
1.2.4 Japan
1.2.5 Southeast Asia
1.2.6 India
1.3 In-memory OLAP Database Market by Type
1.3.1 Transaction
1.3.2 Reporting
1.3.3 Analytics
1.4 In-memory OLAP Database Market by End Users/Application
1.4.1 BFSI
1.4.2 Government and Defense
1.4.3 Healthcare and Life Sciences
1.4.4 Retail and Consumer Goods
1.4.5 Transportation and Logistics
1.4.6 IT and Telecommunication
1.4.7 Manufacturing
1.4.8 Energy and Utility

2 Global In-memory OLAP Database Competition Analysis by Players
2.1 In-memory OLAP Database Market Size (Value) by Players (2013-2018)
2.2 Competitive Status and Trend
2.2.1 Market Concentration Rate
2.2.2 Product/Service Differences
2.2.3 New Entrants
2.2.4 The Technology Trends in Future

3 Company (Top Players) Profiles
3.1 Altibase
3.1.1 Company Profile
3.1.2 Main Business/Business Overview
3.1.3 Products, Services and Solutions
3.1.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.2 IBM
3.2.1 Company Profile
3.2.2 Main Business/Business Overview
3.2.3 Products, Services and Solutions
3.2.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.3 Microsoft
3.3.1 Company Profile
3.3.2 Main Business/Business Overview
3.3.3 Products, Services and Solutions
3.3.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.4 Oracle
3.4.1 Company Profile
3.4.2 Main Business/Business Overview
3.4.3 Products, Services and Solutions
3.4.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.5 SAP SE
3.5.1 Company Profile
3.5.2 Main Business/Business Overview
3.5.3 Products, Services and Solutions
3.5.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.6 Exasol
3.6.1 Company Profile
3.6.2 Main Business/Business Overview
3.6.3 Products, Services and Solutions
3.6.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.7 Jedox
3.7.1 Company Profile
3.7.2 Main Business/Business Overview
3.7.3 Products, Services and Solutions
3.7.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.8 Kognitio
3.8.1 Company Profile
3.8.2 Main Business/Business Overview
3.8.3 Products, Services and Solutions
3.8.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.9 Mcobject
3.9.1 Company Profile
3.9.2 Main Business/Business Overview
3.9.3 Products, Services and Solutions
3.9.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.10 MemSQL
3.10.1 Company Profile
3.10.2 Main Business/Business Overview
3.10.3 Products, Services and Solutions
3.10.4 In-memory OLAP Database Revenue (Million USD) (2013-2018)
3.11 MicroStrategy
3.12 SAS Institute
3.13 Teradata
3.14 Terracotta
3.15 VoltDB

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