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.
Over the next five yearsit is projected that In-memory OLAP Database will register a xx% CAGR in terms of revenue, reach US$ xx million by 2023, from US$ xx million in 2017.
This report presents a comprehensive overview, market shares and growth opportunities of In-memory OLAP Database market by product type, application, key companies and key regions.
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The report also presents the market competition landscape and a corresponding detailed analysis of the major players in the market. The key players covered in this report:
To calculate the market size, LP Information considers value generated from the sales of the following segments:
Segmentation by product type:
Segmentation by application:
Government and Defense
Healthcare and Life Sciences
Retail and Consumer Goods
Transportation and Logistics
IT and Telecommunication
Energy and Utility
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In addition, this report discusses the key drivers influencing market growth, opportunities, the challenges and the risks faced by key players and the market as a whole. It also analyzes key emerging trends and their impact on present and future development.
To study and analyze the global In-memory OLAP Database market size by key regions/countries, product type and application, history data from 2013 to 2017, and forecast to 2023.
To understand the structure of In-memory OLAP Database market by identifying its various subsegments.
Focuses on the key global In-memory OLAP Database players, to define, describe and analyze the value, market share, market competition landscape, SWOT analysis and development plans in next few years.
To analyze the In-memory OLAP Database with respect to individual growth trends, future prospects, and their contribution to the total market.
To share detailed information about the key factors influencing the growth of the market (growth potential, opportunities, drivers, industry-specific challenges and risks).
To project the size of In-memory OLAP Database submarkets, with respect to key regions (along with their respective key countries).
To analyze competitive developments such as expansions, agreements, new product launches and acquisitions in the market.
To strategically profile the key players and comprehensively analyze their growth strategies.
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