In-memory OLAP Database Market, Global Outlook and Forecast 2023-2029
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.
This report aims to provide a comprehensive presentation of the global market for In-memory OLAP 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 In-memory OLAP Database. This report contains market size and forecasts of In-memory OLAP Database in global, including the following market information:
Global In-memory OLAP Database Market Revenue, 2018-2023, 2024-2029, ($ millions)
Global top five companies in 2022 (%)
The global In-memory OLAP 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.
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.
We surveyed the In-memory OLAP 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 In-memory OLAP Database Market, by Type, 2018-2023, 2024-2029 ($ millions)
Global In-memory OLAP Database Market Segment Percentages, by Type, 2022 (%)
MOLAP
DOLAP
SOLAP
Others
Global In-memory OLAP Database Market, by Application, 2018-2023, 2024-2029 ($ millions)
Global In-memory OLAP Database Market Segment Percentages, by Application, 2022 (%)
BFSI
Government and Defense
Healthcare and Life Sciences
Retail and Consumer Goods
Transportation and Logistics
IT and Telecommunication
Manufacturing
Energy and Utility
Global In-memory OLAP Database Market, By Region and Country, 2018-2023, 2024-2029 ($ Millions)
Global In-memory OLAP 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 In-memory OLAP Database revenues in global market, 2018-2023 (estimated), ($ millions)
Key companies In-memory OLAP Database revenues share in global market, 2022 (%)
Further, the report presents profiles of competitors in the market, key players include:
Altibase
IBM
Microsoft
Oracle
SAP SE
Exasol
Jedox
Kognitio
Mcobject
MemSQL
MicroStrategy
SAS Institute
Teradata
Terracotta
VoltDB
Outline of Major Chapters:
Chapter 1: Introduces the definition of In-memory OLAP Database, market overview.
Chapter 2: Global In-memory OLAP Database market size in revenue.
Chapter 3: Detailed analysis of In-memory OLAP 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 In-memory OLAP 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.
