In-Memory Analytics Global Market Report 2024

In-memory analytics involves the process of querying data directly from the random-access memory (RAM) of a computer, as opposed to querying data stored on physical disks. This approach leads to quicker query response times, enabling analytic applications and business intelligence (BI) to facilitate faster business decisions. In-memory analytics contributes to an overall acceleration of BI systems, offering business-intelligence users faster responses compared to traditional disk-based business intelligence, especially for queries that typically take a long time to process in large databases.

The primary categories of in-memory analytics are solutions and services. The solution segment includes the sales of in-memory analytics solutions by entities (organizations, sole traders, and partnerships) offering solutions that eliminate the need to copy, store, or relocate data, thereby enhancing data security. The solution provides an in-memory analytics language, RAQL, suitable for analyzing both large and small datasets. Organizations of various sizes, including large enterprises and small and medium enterprises (SMEs), can deploy these solutions on-premise or in a cloud-based environment. Applications for in-memory analytics span diverse areas such as risk management and fraud detection, sales and marketing optimization, financial management, supply chain optimization, predictive asset management, product and process management, and others (including network management and workforce management). These applications find utility across various industries, including BFSI, retail, IT and telecommunications, manufacturing, government and public sector, and other end-user industries.

The in-memory analytics market research report is one of a series of new reports that provides in-memory analytics market statistics, including in-memory analytics industry global market size, regional shares, competitors with an in-memory analytics market share, detailed in-memory analytics market segments, market trends and opportunities, and any further data you may need to thrive in the in-memory analytics industry. This in-memory analytics market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The in-memory analytics market size has grown exponentially in recent years. It will grow from $4.52 billion in 2023 to $5.66 billion in 2024 at a compound annual growth rate (CAGR) of 25.1%. The expansion observed during the historical period can be attributed to factors such as complex data structures, an enterprise focus on performance, the necessity for real-time insights, a growing demand for interactive data exploration, and the emergence of advanced analytics.

The in-memory analytics market size is expected to see exponential growth in the next few years. It will grow to $14.43 billion in 2028 at a compound annual growth rate (CAGR) of 26.4%. The anticipated growth in the forecast period can be attributed to the increasing expansion of real-time analytics applications, the adoption of in-memory analytics for data lakes, improvements in security and data protection, cross-platform compatibility, and the rise of edge computing and decentralized analytics. Prominent trends expected in the forecast period encompass integration with cloud services, collaboration with IoT analytics, the automation of analytics and machine learning processes, continuous innovation in data storage and processing, and a focus on real-time data processing.

The anticipated growth in the in-memory analytics market is driven by the increasing volume of data. The expanding data volume creates a demand for substantial space in system memory, leading to hindrances and delays in business processes. In response, in-memory analytics is employed to condense data into samples or reduce it to a smaller volume without altering its actual meaning, thereby enhancing query response times. For example, the International Data Corporation (IDC) estimated that 64.2ZB of data was created or copied in 2020, and projections suggest that the data created in the next five years will be more than twice the volume generated since the inception of digital storage. This surge in data is expected to propel the growth of the in-memory analytics market during the forecast period.

The growing adoption of business intelligence tools is poised to drive the in-memory analytics market forward. Business intelligence tools, which collect, analyze, process, and present business data to support decision-making, utilize in-memory analytics for more efficient data processing, analytics, decision-making, insights, and improved business outcomes. A study by Gartner indicates that companies embracing BI tools experience an average 20% increase in revenue due to enhanced market responsiveness and customer-centric decision-making. Consequently, the increased use of business intelligence tools is expected to contribute to the growth of the in-memory analytics market.

A notable trend gaining popularity in the in-memory analytics market is technological advancement. Companies in this market are focusing on developing advanced technologies to reduce operational time and data complexity, providing enhanced products to their clients. For instance, in December 2021, GigaSpaces introduced the InsightEdge portfolio, a set of in-memory computing platforms designed to drive enterprise digital transformation with unique speed, performance, and scale. Coupled with AIOps functionality, this offering facilitates the effortless management and deployment of software platforms catering to demanding analytics processing and enterprise data needs. AIOps, referring to artificial intelligence for IT operations, leverages analytics technology to enhance IT operations.

Major players in the in-memory analytics market are innovating by introducing products like Oracle Fusion Analytics across Customer Exchanges (CX) to meet the increasing demand. Oracle Fusion Analytics across CX aims to enable customers to make faster and better decisions by delivering new capabilities for accelerated insights, enhanced predictions, and improved integrations. Oracle announced the launch of this product in October 2022, emphasizing its potential to provide deeper insights and expedite decision-making into actionable results.

In March 2022, Software AG, a Germany-based software company, acquired StreamSets Inc for approximately €524 million (roughly $580 million). This strategic acquisition is intended to expand Software AG's product offering in the cloud data integration segment of the data integration market. StreamSets Inc, based in the US, operates in the software and technology domain.

Major companies operating in the in the in-memory analytics market report are Amazon Web Services Inc., Oracle Corporation, Qlik Technologies Inc., SAP SE, SAS Institute Inc., Software AG, International Business Machines Corporation, ActiveViam Ltd., Kognitio Holdings Ltd., MicroStrategy Incorporated, ADVIZOR Solutions Inc., EXASOL AG, SnappyData Inc., Teradata Corporation, GigaSpaces Technologies Inc., Information Builders Inc., Hitachi Ltd., Altibase Corp., GridGain Systems Inc., Pivotal Software Inc., TIBCO Software Inc., Altair Engineering Inc., Hazelcast Inc., MemSQL Inc., ScaleOut Software Inc., Aerospike Inc., Couchbase Inc., Redis Labs Inc., VoltDB Inc., Grid Dynamics International Inc.

North America was the largest region in the in-memory analytics market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the in-memory analytics market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa

The countries covered in the in-memory analytics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Canada, Spain.

The in-memory analytics market includes revenues earned by entities by providing solutions that understand, analyze, and derive insights from data stored in random-access memory (RAM) by utilizing multi-core and multi-thread processor capabilities. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified)).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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