In-Memory Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts 2019 - 2029

In-Memory Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts 2019 - 2029

The In-Memory Analytics Market size is estimated at USD 2.98 billion in 2024, and is expected to reach USD 6.93 billion by 2029, growing at a CAGR of 18.38% during the forecast period (2024-2029).

New persistent memory technologies will help reduce the costs and complexity of adopting BMI-enabled architectures (in-memory computing), which is becoming a trend nowadays. Persistent memory represents a new layer of memory between the DRAM and NAND flash memory, which can provide economical mass memory for high-performance workloads. This option can improve application performance, availability, boot times, load methods, and security practices while controlling costs.

Key Highlights

• Digital transformation across all major industries leads to the adoption of real-time analytics as technology trends such as hyper-connectivity, cloud computing, and big data go hand-in-hand with social and business trends. It will enable enterprises to start implementing hybrid transactional/analytical processing (HTAP) strategies, which have the potential to revolutionize data processing by providing real-time insights into big data sets while simultaneously driving down costs.
• The continuously growing volumes of data worldwide create demand for analytics solutions to store, easily access, and analyze this data to generate meaningful insights and make business decisions. In-memory analytics helps organizations overcome the challenges of big data as it is stored in memory that boosts speed and minimizes latency. The emerging technologies further contribute to growing data volume.
• The metaverse, virtual reality, augmented reality, and other emerging technologies are gaining traction nowadays and are expected to further create huge amounts of structured and unstructured data, projected to create demand for in-memory analytics solutions. The growing proliferation of wearables. Smart devices and the Internet of Things fuel the market growth. For instance, according to Cisco, the growth in connected wearable devices, which was forecasted to reach 1,105 million devices in 2022, also contributes to the growing volume of data.
• However, the lack of awareness about the product and higher penetration of conventional analytics tools is restraining the market growth. In-memory may not immediately produce the results; one should desire simply by swapping out technologies and architecture. It requires skills and expertise to manage what's happening, which is profoundly lacking.
• The outbreak of the COVID-19 pandemic accelerated the adoption of digital technologies across all industries and created a huge amount of data which drove the demand for analytics solutions. The increased adoption of AR/VR and smart devices in healthcare due to the COVID-19 pandemic also accelerated the demand for analytics solutions to make data-driven decisions. The successful implementation of such solutions will likely encourage more vendors and businesses to adopt in-memory analytics solutions, paving the way for the studied market's growth during the forecast period.

In-Memory Analytics Market Trends

Manufacturing Sector to Drive the Market Growth

• The manufacturing sector is expected to witness significant growth in the in-memory analytics market. Industry 4.0 and new technology advancements accelerated growth across the manufacturing sector. In-Memory-Analytics (IMA) is increasingly used by many manufacturing organizations to improve manufacturing quality and reduce support costs by enhancing defect tracking and forecasting capabilities to improve supply chains, resulting in overall operational efficiencies.
• The query and reporting performance of the data warehouse should be good. One of the advantages of in-memory databases, such as SAP HANA, is that the transactional data does not necessarily need to be copied to a dedicated data warehouse. Analytical or calculation views can be created over the operational, transactional tables to create a dimensional view that can be used to report and analyze the data.
• In-memory Big Data analytics from enterprise databases is capturing real-time data on change and integrating it with machine data and sensor data to provide a holistic view of operations, thereby enhancing productivity in the manufacturing industry. Data-in-motion is analyzed to react to time-critical operational events, such as traffic or equipment conditions.
• Furthermore, the expanding footprint of manufacturing industry and the increasing awareness about digitization of manufacturing processes are anticipated to support the growth of the studied market. For instance, according to the Department for Promotion of Industry and Internal Trade (India) and MOSPI, the annual growth rate of production in the manufacturing industry increased by 11.40% in FY22.
• Moreover, the connected factory is at the center to the future of manufacturing, as it enables devices and elements to communicate in order to gain a better understanding of each process. Implementing analytics is an essential component of a connected factory. The increased smart factories where the technology enables machines, personnel and sensors to exchange information in a seamless and automated manner throughout the manufacturing process. Data generated by connected equipment generates a vast amount of information, and with the aid of edge connectivity and computational technology, this information can be analysed and understood in radically new ways.

Asia-Pacific to Witness Significant Growth

• The in-memory analytics market in the Asia-Pacific region is driven by the growing digitization of end-users and the rising adoption of cost-effective cloud-based analytical software by SMBs, especially in China and India.
• Countries such as China, India, and Japan act as hubs for enterprises such as BPOs and KPOs and are also known as manufacturing factories worldwide. The very basic foundation of such organizations is the huge quantities of data that need to be stored, analyzed, and used for decision-making. This drives the demand for the in-analytics market.
• Mobile technology and services continue to play an important role in the economy of Asia-Pacific. The growing awareness and a surge in 4G and 5G coverage across the region also accelerate the demand for analytics solutions. For instance, according to VIAVI Solutions, China was the leading country in the Asia-Pacific region in terms of 5G availability in most cities, as the country had 356 cities covered by 5G in 2022, followed by countries such as the Philippines (105), and South Korea (85), among others.
• Apart from this, government initiatives promoting the adoption of digital solutions also drive the growth of the studied market in the Asia-Pacific region. For instance, the Indian government uses big data for various purposes, such as getting an estimate of trade in the country, urbanization analysis, and unreserved railway passengers analysis. To maintain its edge and sustain its growth, China's economy may also enhance its adoption of advanced technologies to a higher value and in more advanced industries, with big data as one of the instruments to facilitate this shift, which will aid the growth of the studied market in the Asia-Pacific region.

In-Memory Analytics Industry Overview

The in-memory analytics market is competitive as several key players and new entrants form a competitive landscape, accounting for a substantial market share. Also, strategic partnerships, acquisitions, and new launches of product/technology are increasing high rivalry in the market. SAP SE, IBM Corporation, SAS Institute, Inc., and others are key players.

In April 2023, SAP SE updated its SAP HANA 2.0 SPS 0.7 with significant features such as enhanced machine learning capabilities, updated SDA/SDI adapter certifications, new data provisioning capabilities, backup & recovery with retention periods, and others. The newest version of SAP HANA offers many improvements in terms of TCO, scalability, reliability, and user experience. It streamlines and democratizes in-memory computing, allowing even more people within your organization to get quick responses and valuable insights.

In March 2023, Exasol announced new releases and enhancements to its In-Memory Analytics Database. The company states that the new release demonstrates its dedication to providing its customers with a solution that does not necessitate compromise between cost, performance, and flexibility.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support