Global In-Memory Database Market is expected to reach US$ XX Bn by 2026 at a CAGR of XX % during the forecast period. The report includes the analysis of impact of COVID-19 lock-down on the revenue of market leaders, followers, and disrupters. Since lock down was implemented differently in different regions and countries, impact of same is also different by regions and segments. The report has covered the current short term and long term impact on the market, same will help decision makers to prepare the outline for short term and long term strategies for companies by region. know about the Research Methodology:-Request Free Sample Report In-memory databases are primarily used in big data management and business analytics where there is a need for storage and fast data access. In-memory databases are faster as compare to traditional databases. An in-memory database is a part of the computer main memory and needs just fewer instructions to access the data for writing and reading. Another advantage of an in-memory database system is its application in real-time embedded systems which are highly resource-constrained which have low processor computational capabilities and require small memory. Furthermore, A massive amount of data being generated from various industries, falling RAM prices, faster data processing are some of the major driving factors expected to propel the in-memory database market around the world. However, Lack of standards and memory space constraints are some of the restraining factors that may hinder the growth of the in-memory database market. The data security concerns and volatile nature of memory are some of the stumbling blocks in the adoption of in-memory database solutions. In applications, the transaction segment is expected to hold the larger market size during the forecast period, due to the rising e-commerce industry uses non-cash payments mode across the world increasing the transaction application, in the market. By the processing type segment is divided into Online Analytical Processing (OLAP), Online Transaction Processing (OLTP). Among these, OLAP systems are expected to grow at the highest CAGR during the forecast period. OLAP systems are typically deployed for reporting and Business Intelligence (BI), sales management, forecasting, and business process management. In-memory OLAP solutions help to address big data challenges for organizations. In terms of the deployment model, the On-premises deployment model is expected to hold a larger market share during the forecast period. The on-premises deployment model provides privacy parameters and confidentiality to the organizational data; hence, most of the organizations are adopting the on-premises deployment model. The on-demand deployment model is expected to grow at the highest CAGR during the forecast period, because of agility, cost-effectiveness, and affordability it offers to the end customer.

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Global In-Memory database market, by Application:

• Transaction
• Reporting
• Analytics
• Others

Global In-Memory database market, by Data Type:

• Relational
• NewSQL

Global In-Memory database market, by Processing Type:

• Online Analytical Processing (OLAP)
• Online Transaction Processing (OLTP)

Global In-Memory database market, by Deployment Model:

• On-Premises
• On-Demand

Global In-Memory database market, by Organization Size:

• Large Enterprises
• Small and Medium Enterprises

Global In-Memory database market, by Vertical:

• Healthcare and Life Sciences
• Government and Defense
• Transportation and Logistics
• Retail and Consumer Goods
• Manufacturing
• IT and Telecommunication
• Energy and Utility
• Others

Global In-Memory database market, by Region:

• North America
• Europe
• Asia-Pacific (APAC)

Key Players of the Global In-Memory Database Market:

• IBM Corporation
• Microsoft Corporation
• Oracle Corporation
• Teradata Corporation
• Amazon Web Services
• Tableau Software
• Kognitio Ltd.
• VoltDB
• DataStax
• McObject LLC
• Altibase Corporation
• Activeviam
• Aerospike
• MemSQL
• Sqlite
• Starcounter
• Pointillist
• Quadient
• Kitewheel

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