查看購物車
  • Simplified Chinese
  • English
  • Japanese
封面
市場調查報告書
商品編碼
1641907

記憶體內分析：市場佔有率分析、產業趨勢與統計、成長預測（2025-2030）

In-Memory Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

價格

※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

簡介目錄

記憶體內分析市場規模預計在 2025 年為 35.3 億美元，預計到 2030 年將達到 82 億美元，預測期內（2025-2030 年）的複合年成長率為 18.38%。

記憶體分析-市場-IMG1

新的持久記憶體技術有助於降低採用支援 BMI 的架構（記憶體內運算）的成本和複雜性，這是一種新興趨勢。持久記憶體是 DRAM 和NAND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容量記憶體。此選項可在控制成本的同時提高應用程式的效能、可用性、啟動時間、載入行為和安全性。

主要亮點

  • 由於超連接、雲端運算和巨量資料等技術趨勢與社會和商業趨勢緊密相連，每個主要行業的數位轉型都將導致即時分析的採用。這將鼓勵公司開始實施混合事務/分析處理 (HTAP) 策略。 HTAP 策略有可能透過提供對巨量資料集的即時洞察來徹底改變資料處理，同時有助於降低成本。
  • 全球資料量不斷成長，對分析解決方案的需求也隨之增加，以便儲存、輕鬆存取和分析這些資料，從而產生有意義的見解並做出業務決策。記憶體內分析有助於克服巨量資料挑戰。記憶體內分析將資料儲存在記憶體中，從而提高處理速度並最大限度地減少延遲。新技術也促進了資料量的增加。
  • 元宇宙、虛擬實境、擴增實境和其他新興技術目前正在迅速普及，預計將產生更多的資料，從而產生對記憶體內分析解決方案的需求。穿戴式裝置的普及。智慧設備和物聯網將推動市場成長。例如，連網穿戴裝置的興起也推動了資料量的增加。
  • 然而，產品認知度低和傳統分析工具滲透率高阻礙了市場的成長。記憶體內並不是僅僅透過切換到不同的技術和架構就能產生立竿見影的效果。要做到這一點，你需要具備管理正在發生的事情的技能和專業知識，但這些技能和專業知識卻嚴重短缺。
  • COVID-19 疫情的爆發加速了各行各業對數位技術的採用，產生了大量資料並推動了對分析解決方案的需求。 COVID-19 疫情也推動了醫療保健領域對 AR/VR 和智慧型裝置的採用，加速了對做出資料主導決策的分析解決方案的需求。成功實施此類解決方案可能會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平道路。

記憶體內分析市場的趨勢

製造業推動市場成長

  • 預計製造業將見證記憶體內分析市場的顯著成長。工業 4.0 和新技術的進步正在加速整個製造業的成長。許多人正在使用記憶體內分析 (IMA) 透過增強缺陷追蹤和預測功能來改善供應鏈，從而提高生產品質、降低支援成本並提高整體業務效率。
  • 資料倉儲查詢和彙報效能必須良好。 SAP HANA 等記憶體內的一個優點是交易資料不一定需要複製到專用資料倉儲。可以在操作事務表之上建立分析視圖和計算視圖，以建立可用於報表和分析資料的維度視圖。
  • 企業資料庫的記憶體內體巨量資料分析可擷取有關變化的即時資料，並將其與資料和感測器資料整合，以提供整體營運視圖並提高製造生產率。分析動態資料可讓您回應時間關鍵的營運事件，例如交通狀況或資產狀態。
  • 此外，不斷擴大的製造足跡和對製造過程數位化的認知不斷增強預計將推動所調查市場的成長。例如，根據工業和國內貿易促進部和 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，互聯工廠對於製造業的未來至關重要，它使設備和元素能夠通訊，從而更深入地了解每個流程。分析的實施是互聯工廠的重要組成部分。智慧工廠正在興起，技術使機器、人員和感測器能夠在整個生產過程中以無縫、自動化的方式交換資訊。連接設備產生的資料產生了大量的資訊，借助邊緣連接和計算技術，這些資訊可以以全新的方式來分析和理解。

亞太地區成長強勁

  • 亞太地區記憶體內分析市場的發展受到終端用戶數位化程度不斷提高以及中小型企業（尤其是中國和印度）擴大採用具有成本效益的雲端基礎的分析軟體的推動。
  • 中國、印度和日本等國家是 BPO 和 KPO 等公司的中心，也被稱為全球製造工廠。此類組織的基本基礎是需要儲存、分析和使用大量資料來進行決策。這正在推動分析市場的需求。
  • 行動技術和服務繼續在亞太地區經濟中發揮重要作用。全部區域對 4G 和 5G 的認知度不斷提高和快速採用也推動了對分析解決方案的需求。例如，根據 VIAVI Solutions 的數據，到 2022 年，中國將有 356 個城市覆蓋 5G，其次是菲律賓（105 個城市）和韓國（85 個城市）。
  • 除此之外，政府推動數位解決方案採用的措施也推動了亞太地區研究市場的成長。例如，印度政府將巨量資料用於多種用途，包括國內貿易估計值、都市化分析和鐵路客運量分析。為了保持主導地位並維持成長，中國經濟可能會加大在高價值和更先進行業中採用先進技術，而巨量資料是促進這一轉變的槓桿之一。研究市場。

記憶體內分析行業概覽

記憶體內分析市場競爭激烈，幾個主要企業和新參與企業塑造了競爭格局並佔據了相當大的市場佔有率。此外，策略夥伴關係、收購和新產品/技術的推出加劇了市場競爭。主要企業包括 SAP SE、IBM Corporation 和 SAS Institute, Inc.

2023 年 4 月，SAP SE 將更新 SAP HANA 2.0 SPS 0.7，以包含增強的機器學習功能、更新的 SDA/SDI 適配器認證、新的資料配置功能以及具有保留期的備份和復原等重要功能。 SAP HANA 最新版本在 TCO、可擴展性、可靠性和使用者體驗方面做出了許多改進。透過簡化和民主化記憶體內運算，組織內的更多人可以獲得更快的回應和有價值的見解。

2023 年 3 月，Exasol 宣布發布其記憶體分析資料庫的新版本並增強其功能。該公司表示，新產品表明了其致力於為客戶提供不需要在成本、性能和靈活性之間做出妥協的解決方案。

其他福利

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

目錄

第 1 章 簡介

  • 研究假設和市場定義
  • 研究範圍

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
    • 購買者/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
    • 競爭對手之間的競爭強度

第5章 市場動態

  • 市場促進因素
    • 最終用戶數位轉型推動即時分析的採用
    • 資料量不斷增加需要快速分析方法
    • 計算技術的進步
  • 市場限制
    • 缺乏最終使用者意識

第6章 市場細分

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

第7章 競爭格局

  • 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 市場機會與未來趨勢

第9章投資分析

簡介目錄
Product Code: 62302

The In-Memory Analytics Market size is estimated at USD 3.53 billion in 2025, and is expected to reach USD 8.20 billion by 2030, at a CAGR of 18.38% during the forecast period (2025-2030).

In-Memory Analytics - Market - IMG1

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