Exploring Market Competitive Outlook, Growth Opportunities and Technologies in the In-Memory Analytics Market

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 growth in the historic period can be attributed to complex data structures, enterprise focus on performance, need for real-time insights, demand for interactive data exploration, rise 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 growth in the forecast period can be attributed to increasing growth in real-time analytics applications, in-memory analytics for data lakes, enhanced security and data protection, cross-platform compatibility, edge computing and decentralized analytics.. Major trends in the forecast period include integration with cloud services, integration with iot analytics, automated analytics and machine learning, continuous innovation in data storage and processing, real-time data processing.

Market Overview -
The in-memory analytics refer to a process of querying data when it resides in the compute''s random-access memory (RAM), as opposed to querying the data that is stored on physical disks. This results in shortened query response times, allowing analytic applications and business intelligence (BI) to support faster business decisions. In-memory analytics helps in increasing the overall speed of a BI system and provides business-intelligence users with faster answers compared to traditional disk-based business intelligence, particularly for queries that take a long time to process in a large database.

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Rising Data Volumes Propel In-Memory Analytics Market Growth As Demands For Efficient Data Processing Soar
The growing volume of data is expected to drive the growth of the in-memory analytics market. Growing data volume is increasing demand for large space in the system's memory which leads to obstruction and delay in the business process. In-memory analytics is used to minimise the data into samples or reduce the data to a small volume by not changing the actual meaning and increasing the query response time. For instance, the International Data Corporation (IDC), a US-based examiner of the consumer market, estimated that 64.2ZB of data was created or copied in 2020. The amount of data created throughout the next five years will be larger than twice the volume of data created since the advent of digital storage. This is likely to drive the in-memory analytics market growth during the forecast period.

Competitive Landscape -
Major companies operating 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.

Gigaspaces Launches Insightedge For Enhanced Performance And Scale
Technological advancement is a growing trend that is gaining key popularity in the in-memory analytics market. The companies operating in the in-memory analytics market are developing advanced technologies that will help in reducing the time for operation and complexity of the data by providing an enhanced product to their clients. For instance, In December 2021, GigaSpaces, a US-based software company, announced the launch of the InsightEdge portfolio, a new set of in-memory computing platforms that are designed to drive the enterprise digital transformation with unique speed, performance, and scale. Combined with the AIOps functionality, GigaSpaces will deliver effortless management and deployment of a portfolio of software platforms that meet the most stimulating analytics processing and enterprise data needs. AIOps refers to artificial intelligence for IT operations that provides analytics technology and enhances IT operations.

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Key Segments -

The in-memory analytics market covered in this report is segmented -

1) By Component: Solution, Service
2) By Organization Size: Large Enterprises, Small and medium Enterprises (SME's)
3) By Deployment Mode: On-premise, Cloud-Based

Key highlights covered in the report -
1. Detailed market size forecast and historical data analysis
2. Key drivers influencing market growth
3. Identification of upcoming trends and potential opportunities in the market
4. Analysis of major players strategies, to understand competitive dynamics and market positioning
5. Evaluation of regional dynamics

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