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1433501

記憶體內分析 -市場佔有率分析、產業趨勢/統計、成長預測（2024-2029）

In-Memory Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

記憶體內分析市場規模預計到 2024 年為 29.8 億美元，預計到 2029 年將達到 69.3 億美元，在預測期內（2024-2029 年）將成長 18.38%，複合年成長率成長。

記憶體分析 - 市場

新的持久記憶體技術可以幫助降低採用支援 BMI 的架構（記憶體內運算）的成本和複雜性，目前已成為一種趨勢。持久記憶體代表了 DRAM 和NAND快閃記憶體快閃記憶體之間的新記憶體層，可以為高效能工作負載提供經濟的大記憶體容量。此選項可讓您提高應用程式效能、可用性、啟動時間、載入方法和安全實踐，同時控制成本。

主要亮點

  • 超連結、雲端運算和巨量資料等技術趨勢與社會和商業趨勢密切相關，主要產業的數位轉型正在推動即時分析的採用。這將使企業能夠開始實施混合事務/分析處理（HTAP）策略，該策略可以透過提供對巨量資料集的即時洞察同時降低成本來徹底改變資料處理。
  • 隨著全球資料量持續成長，需要分析解決方案來儲存這些資料、輕鬆存取和分析資料、產生有意義的見解並做出業務決策。記憶體內分析可幫助組織克服巨量資料挑戰，因為巨量資料儲存在記憶體中，從而提高速度並最大限度地減少延遲。新技術進一步促進了資料量的成長。
  • 元宇宙、虛擬實境、擴增實境和其他新興技術如今越來越受到關注，預計將進一步創建資料結構化和非結構化資料，從而創造對記憶體內分析解決方案的需求。穿戴式裝置快速成長。智慧設備和物聯網將推動市場成長。例如，根據思科的預測，到 2022 年，連網連網型穿戴式裝置裝置的成長預計將達到 11.05 億台，這也促進了資料量的成長。
  • 然而，產品意識的缺乏和傳統分析工具的高度普及正在限制市場的成長。記憶體內的結果可能不會立即出現。只需交換技術和架構即可實現。管理正在發生的事情需要技能和專業知識，而這在很大程度上是缺乏的。
  • COVID-19感染疾病流行的爆發加速了數位技術在所有行業的採用，產生了大量資料，推動了對分析解決方案的需求。由於 COVID-19感染疾病， AR/VR 和智慧型裝置在醫療保健領域的採用不斷增加，也加速了對分析解決方案的需求，以做出資料主導的決策。此類解決方案的成功實施可以鼓勵更多供應商和企業採用記憶體內分析解決方案，為預測期內研究市場的成長鋪路。

記憶體內分析市場趨勢

製造業推動市場成長

  • 在製造業中，記憶體內分析市場預計將大幅成長。工業 4.0 和新技術進步加速了整個製造業的成長。記憶體分析（IMA）透過增強缺陷追蹤和預測能力來改善供應鏈並提高整體營運效率，從而提高製造品質並降低支援成本，它擴大在許多製造組織中使用。
  • 資料倉儲的查詢和報表效能必須良好。 SAP HANA 等記憶體內的好處之一是交易資料不一定需要複製到專用資料倉儲。您可以在操作表和交易表上建立分析或計算視圖，以建立可用於報表和分析資料的維度視圖。
  • 來自企業資料庫的記憶體內巨量資料分析透過捕獲有關變化的即時資料並將其與資料和感測器資料整合以提供整體情況的業務情況來提高製造生產力。分析動態資料以回應時間關鍵的操作事件，例如交通狀況和設備運作狀況。
  • 此外，擴大製造規模和提高製造流程數位化意識預計將支持所研究市場的成長。例如，根據印度產業內貿易促進部和 MOSPI 的數據，22 會計年度製造業年產量成長率成長了 11.40%。
  • 此外，連網型工廠將成為未來製造業的核心，因為它們允許設備和元件進行通訊，以更深入地了解每個流程。實施分析是連網型工廠的關鍵組成部分。隨著智慧工廠的興起，科技使機器、人員和感測器能夠在整個製造過程中以無縫和自動化的方式交換資訊。互聯設備產生的資料會產生大量資訊，借助邊緣連接和運算技術，可以以全新的方式分析和理解這些資訊。

亞太地區將經歷顯著成長

  • 亞太記憶體內分析市場的推動因素是最終用戶數位化程度的提高以及中小型企業（尤其是中國和印度）擴大採用經濟高效的雲端基礎的分析軟體。
  • 中國、印度和日本等國家是 BPO 和 KPO 等公司的中心，在全球也被稱為製造工廠。此類組織的根本基礎是需要儲存、分析和用於決策的大量資料。這將增加對分析市場的需求。
  • 行動技術和服務繼續在亞太地區經濟中發揮重要作用。全部區域意識的提高以及 4G 和 5G 覆蓋範圍的擴大也加速了對分析解決方案的需求。例如，根據VIAVI Solutions的數據，截至2022年，中國在大多數城市的5G可用性方面是亞太地區領先的國家，5G覆蓋的城市有356個，菲律賓（105個）等緊隨其後。 、韓國（85）等
  • 除此之外，政府促進數位解決方案採用的措施也將推動亞太地區研究市場的成長。例如，印度政府將巨量資料用於各種目的，例如估計國內貿易、分析都市化以及分析鐵路上的旅客。中國經濟將利用巨量資料作為推動這項變革的手段之一，並在更高價值和更先進的行業中加強先進技術的採用，以保持其優勢並維持成長，這將有助於研究領域的發展。亞太市場。

記憶體內分析產業概述

記憶體內分析市場競爭激烈，幾個主要企業和新進者形成了競爭形勢，佔據了重要的市場佔有率。此外，策略聯盟、收購和新產品/技術的推出也加劇了市場競爭。主要參與者包括 SAP SE、IBM Corporation 和 SAS Institute, Inc.。

2023 年 4 月，SAP SE 更新了 SAP HANA 2.0 SPS 0.7，增加了重要功能，例如增強的機器學習功能、更新的 SDA/SDI 適配器認證、新的資料調配功能以及保留的備份和復原功能。 SAP HANA 的最新版本在 TCO、可擴展性、可靠性和使用者體驗方面進行了許多改進。簡化和民主化記憶體內運算，使組織中的更多人能夠獲得更快的回應和有價值的見解。

2023 年 3 月，Exasol 宣布了其記憶體內分析資料庫的新版本和增強功能。該公司表示，這個新版本體現了其致力於為客戶提供在成本、性能和彈性之間不妥協的解決方案的決心。

其他福利

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業價值鏈分析
  • 產業吸引力－波特五力分析
    • 買家/消費者的議價能力
    • 供應商的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間敵對關係的強度

第5章市場動態

  • 市場促進因素
    • 最終用戶數位轉型導致採用即時分析
    • 不斷增加的資料量需要快速的分析方法
    • 計算技術的進步
  • 市場限制因素
    • 最終使用者缺乏意識

第6章市場區隔

  • 按配置
    • 本地
    • 雲
  • 按最終用戶產業
    • BFSI
    • 零售
    • 資訊科技/通訊
    • 製造業
    • 政府/公共機構
    • 其他最終用戶產業
  • 按地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東/非洲

第7章 競爭形勢

  • 公司簡介
    • SAP SE
    • IBM Corporation
    • Oracle Corporation
    • Activeviam
    • Amazon Web Services, Inc.
    • Information Builders, Inc.
    • Kognitio Ltd.
    • Microstrategy Incorporated
    • SAS Institute, Inc.
    • Software AG

第8章 市場機會及未來趨勢

第9章投資分析

簡介目錄
Product Code: 62302

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).

In-Memory Analytics - Market

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

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Value Chain Analysis
  • 4.3 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.3.1 Bargaining Power of Buyers/Consumers
    • 4.3.2 Bargaining Power of Suppliers
    • 4.3.3 Threat of New Entrants
    • 4.3.4 Threat of Substitute Products
    • 4.3.5 Intensity of Competitive Rivalry

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Digital Transformation of End-users Leading to Adoption of Real-Time Analytics
    • 5.1.2 Growing Data Volume Demanding Swift Analytical Methods
    • 5.1.3 Advancements in Computational Technology
  • 5.2 Market Restraints
    • 5.2.1 Lack of Awareness in End-users

6 MARKET SEGMENTATION

  • 6.1 By Deployment
    • 6.1.1 On-Premise
    • 6.1.2 Cloud
  • 6.2 By End-user Industry
    • 6.2.1 BFSI
    • 6.2.2 Retail
    • 6.2.3 IT and Telecommunications
    • 6.2.4 Manufacturing
    • 6.2.5 Government and Public Sector
    • 6.2.6 Other End-user Industries
  • 6.3 By Geography
    • 6.3.1 North America
    • 6.3.2 Europe
    • 6.3.3 Asia-Pacific
    • 6.3.4 Latin America
    • 6.3.5 Middle East & Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 SAP SE
    • 7.1.2 IBM Corporation
    • 7.1.3 Oracle Corporation
    • 7.1.4 Activeviam
    • 7.1.5 Amazon Web Services, Inc.
    • 7.1.6 Information Builders, Inc.
    • 7.1.7 Kognitio Ltd.
    • 7.1.8 Microstrategy Incorporated
    • 7.1.9 SAS Institute, Inc.
    • 7.1.10 Software AG

8 MARKET OPPORTUNITIES AND FUTURE TRENDS

9 INVESTMENT ANALYSIS