[160 Pages Report] The overall in-memory database market is expected to grow from USD 2.10 billion in 2015 to USD 6.58 billion by 2021, at a CAGR of 19.3% from 2016 to 2021.

In-memory database refers to the technology that stores the data fully or partially in the memory on either single or distributed servers. The In-Memory Database technology keeps the whole database in the main memory of the system. The technology supports the transactional, operational, and analytical workloads. It helps in reducing latency in the data, which further helps in extraction of data for its processing on real-time basis. Moreover, the massive amount of data (big data) is being generated across various industries. The need for analyzing this data in real time has been fulfilled by in-memory database solutions, as these solutions provide quick accessibility and processing of data.

Being a growing sub-set of the Database Management System (DBMS), in-memory database has the capability of working with data in memory rather than reading and writing it from the file system. With an in-built capability of performing data management functions at a faster magnitude, the in-memory database has lower memory and Central Processing Unit (CPU) requirements. Moreover, unlike traditional disk-based systems, the in-memory database system carries no file Input/output (I/O) burden. Due to the aforesaid features and capabilities of in-memory database systems, the market has shown significant growth in various enterprises.

The base year considered for the study is 2015, and the forecast has been provided for the period between 2016 and 2021.

In-Memory Database Market Dynamics

Drivers

Faster data processing

Falling RAM prices

Masive amount of data being generated from various industries

Restraints

Memory space constraints

Lack of standards

Opportunities

Non-embedded applications requiring exceptional performance

Emergence of Hybrid Transactional and Analytical Processing (HTAP)

Increasing demand for real-time processing

Challenges

Volatile nature of memory

Data security concerns

Faster data processing, falling RAM prices, and massive amount of data being generated from various industries drives the global in-memory database market

BFSI, government & defense, and retail & consumer are few of the verticals which have shown tremendous adoption of in-memory database systems. This is due to the data-centric characteristics of these verticals. Apart from this, the healthcare and life sciences industry has shown significant growth rate during the forecast period. There are various opportunities prevailing in this market, which include non-embedded applications requiring exceptional performance, emergence of Hybrid Transactional & Analytical Processing (HTAP), and increasing demand for real-time processing. On the other hand, the market also has a few challenges, such as volatile nature of memory and data security concerns.

The following are the major objectives of the study.

To describe and forecast the in-memory database market, in terms of value, by application, data type, processing type, deployment model, organization size, vertical and region

To describe and forecast the market, in terms of volume, by type and application

To describe and forecast the reed sensor market, in terms of value, by region�Asia Pacific (APAC), Europe, North America, Middle East and Africa (MEA), and Latin America along with their respective countries

To provide detailed information regarding major factors influencing market growth (drivers, restraints, opportunities, and challenges)

To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the overall market

To study the complete value chain of in-memory database

To analyze opportunities in the market for stakeholders by identifying the high-growth segments of the in-memory database ecosystem

To strategically profile key players and comprehensively analyze their market position in terms of ranking and core competencies, along with detailing competitive landscape for market leaders

To analyze strategic approaches such as product launches, acquisitions, contracts, agreements, and partnerships in the in-memory database market

During this research study, major players operating in the in-memory database market in various regions have been identified, and their offerings, regional presence, and distribution channels have been analyzed through in-depth discussions. Top-down and bottom-up approaches have been used to determine the overall market size. Sizes of the other individual markets have been estimated using the percentage splits obtained through secondary sources such as Hoovers, Bloomberg BusinessWeek, and Factiva, along with primary respondents. The entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews with industry experts such as CEOs, VPs, directors, and marketing executives for key insights (both qualitative and quantitative) pertaining to the market. The figure below shows the breakdown of the primaries on the basis of the company type, designation, and region considered during the research study.

To know about the assumptions considered for the study, download the pdf brochure

The in-memory database market comprises a network of players involved in the research and product development; distribution and sale; and post-sales services. Key players considered in the analysis of the in-memory database market are Microsoft (US), IBM (US), Oracle (US), SAP SE (Germany), Teradata (US), Amazon Web Services (US), Tableau (US), Kognitio (UK), VoltDB (US), DataStax (US), ENEA (Sweden), McObject (US) and Altibase (South Korea).

Major In-Memory Database Market Developments:

In November 2016, SAP launched IoT Application Enablement solution. The SAP HANA Cloud Platform IoT service facilitates customers to develop IoT solutions effectively and achieve fast time to value.

In October 2015, Oracle launched a new set of Oracle Database Cloud Services which further expands its portfolio of Oracle Cloud Platform Services. This enables customers to leverage from real-time transaction processing through Oracle Database In-Memory on-cloud.

In May 2013, Teradata launched Teradata Intelligent memory, a database technology that is instrumental in delivering high speed in-memory performance at a cost-effective way. The software helps customers to configure exact amount of in-memory capability required to handle critical workloads.

Target Audience

Independent Software Vendors

Business Analytics Software Providers

Application Design and Software Developers

System Integrators

IT Service Providers

Cloud Service Providers

Report Scope:

By Application:

Transaction

Reporting

Analytics

Others

By Data Type:

Relational

NoSQL

NewSQL

By Processing Type:

Online Analytical Processing (OLAP)

Online Transaction Processing (OLTP)

By Deployment Model:

On Premise

On Demand

By Organization Size:

Large Enterprises

Small and Medium Enterprises

By Vertical:

Healthcare and Life Sciences

BFSI

Manufacturing

Retail and Consumer Goods

IT and Telecommunication

Transportation

Media and Entertainment

Energy and Utilities

Government and Defense

Academia and Research

By Region:

North America

Europe

Asia Pacific (APAC)

MEA

Latin America

Critical questions which the report answers

What are new application areas which the in-memory database companies are exploring?

Which are the key players in the market and how intense is the competition?

Available Customizations:

Based on the given market data, MarketsandMarkets offers customizations in the reports as per the client�s specific requirements. The available customization options are as follows:

Product Analysis:

Product matrix gives a detailed comparison of product portfolio of each company.

Geographic Analysis:

Further breakdown of the North America In-Memory Database Market

Further breakdown of the Europe in-memory database market

Further breakdown of the APAC market

Further breakdown of the MEA market

Further breakdown of the Latin America market

Company Information:

Detailed analysis and profiling of additional market players

The overall in-memory database market is expected to grow from USD 2.10 billion in 2015 to USD 6.58 billion by 2021, at a CAGR of 19.3% from 2016 to 2021. Faster data processing, falling RAM prices, and massive amount of data being generated from various industries are the drivers that propel the growth of the market.

In-memory database refers to the technology that stores the data fully or partially in the memory on either single or distributed servers. The in-Memory Database technology keeps the whole database in the main memory of the system. The technology supports the transactional, operational, and analytical workloads. It helps in reducing latency in the data, which further helps in extraction of data for its processing on real-time basis. Moreover, the massive amount of data (big data) is being generated across various industries. The need for analyzing this data in real time has been fulfilled by in-memory database solutions, as these solutions provide quick accessibility and processing of data.

The in-memory database market in APAC is expected to grow at the highest CAGR during the forecast period. APAC is the fastest-growing market for in-memory database. Many Asian countries are leveraging from information-intensive technologies to gain edge over competition. Major countries in APAC such as India, China, and others are digitalizing and promoting the emerging technologies such as mobility, IoT, cloud, BI, and analytics. This has provided tremendous opportunities for the growth of in-memory database market. Hence, there are outstanding chances for the growth of data being generated from connected devices. It provides a major opportunity for in-memory database vendors as data-centric enterprises will require faster analytics and timely access to data, more than ever.

Faster data processing, falling RAM prices, and massive amount of data being generated from various industries drives the global in-memory database market

Faster data processing

In-memory processing is the technology used for faster processing of data by storing it in the main memory databases and is increasingly recommended to meet the Business Intelligence (BI) needs. Hence, the in-memory processing technology has helped the in-memory database market to gain traction among businesses of all sizes across industries, particularly in the field of data analytics. Faster processing of data leverages organizations with broader customer insights, helping companies to offer differentiated products and services to meet specific customer needs.

Falling RAM prices

An in-memory database has gained traction owing to the reduced prices of computer memory and increasing shift towards the use of analytics solutions for decision making, as businesses of every size are expecting immediate response times. Furthermore, the decline in the semiconductor technologies and rapid maturation of infrastructure of computing technologies are some other factors driving the use of in-memory databases. This has made in-memory database budget-friendly, making it feasible across various businesses, particularly SMEs.

Massive amount of data being generated from various industries such as BFSI, government & defense, and retail & consumer goods

The BFSI vertical is expected to have the largest market size in the in-memory database market. The BFSI vertical has witnessed high adoption of in-memory databases as they are well-suited and capable enough to handle high speed transactions available in various industries such as BFSI.

The retail & consumer goods vertical is expected to grow at the highest CAGR during the forecast period. In-memory databases with their rapid data processing capabilities will enable retailers to utilize real-time analytics to drive better insights into business processes and their customers; leading to optimized operations, and improved decision-making.

Due to the increasing workload and rising threats, the government and defense have relied on immediate decision-making through real-time data processing. In-memory database technologies are playing a vital role to attain operational efficiency in these sectors.

Real-time analytics has influenced the defense sector for making right decision in time. For this tremendous data is needed to analyze the information about different vehicles used in war, opposition strengths or any movement, location tracking, and other historical information related to the war to make the right move at the right time during the war. Thus, real-time data analytics is very important to manage extreme situation which arise in the defense sector.

Critical questions the report answers:

Where will all these developments take the industry in the mid to long term?

What are the upcoming industry applications for in-memory databases?

The memory space constraints and lack of standards are major factor restraining the growth of the in-memory database market.

In terms of analytical functions for various applications, such as big data applications which have been defined by petabytes of data; In-memory database solutions have provided limited memory space. This is due to memory space constraints on the size of in-memory databases, which depends on the amount of RAM physically available in the server. For example, if a database size is under 3 GB on 32-bit OS platforms, it is limited by the 32-bit address space. For 64-bit OS platforms, the database size will depend on the physical memory available in the system. . In most cases, the in-memory databases are designed as per specific application requirements and are developed and adapted accordingly.

The performance of data accessibility on in-memory database is still limited by the architecture of the application driving it. Sometimes, the structure and implementation of a database, the hardware on which the database runs, and the connectivity to the external devices may create problem in the overall processing performance of the in-memory solutions. For example, an expert on an in-memory database specific to a use case cannot be an expert in another, due to difference in data structure and the way data is stored & accessed.

Key players considered in the analysis of the in-memory database market are Microsoft (US), IBM (US), Oracle (US), SAP SE (Germany), Teradata (US), Amazon Web Services (US), Tableau (US), Kognitio (UK), VoltDB (US), DataStax (US), ENEA (Sweden), McObject (US) and Altibase (South Korea). These players are increasingly undertaking product launches and product upgradations to develop and introduce new technologies and products in the market.

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