엣지 애널리틱스 시장 : 시장 점유율 분석, 산업 동향, 통계, 성장 예측(2025-2030년)

The edge analytics market size stands at USD 17.30 billion in 2025 and is on track to reach USD 52.04 billion by 2030, reflecting a 24.64% CAGR.

Growth is propelled by the rapid expansion of IoT end-points, wider 5G coverage that supports low-latency data paths, and ongoing advances in AI-enabled silicon that places inference engines at the network edge. Vendors are prioritizing ruggedized micro-data centers, liquid-cooling designs, and federated learning frameworks that keep sensitive data local while still training global models. Enterprises are also integrating cloud-native orchestration tools to standardize application delivery across thousands of edge nodes, thereby compressing deployment cycles and raising ROI expectations. The edge analytics market is further influenced by regulatory drives toward data-sovereign architectures, especially in healthcare and finance where real-time decision support must coexist with strict privacy mandates.

Global Edge Analytics Market Trends and Insights

Proliferation of IoT end-points

The global device base is generating 328.77 million TB of data every day, forcing analytics to migrate toward local processing so that bandwidth is conserved and insights arrive in real time. Industrial plants now stream vibration and temperature metrics from millions of sensors, and edge accelerators running optimized models handle this influx with sub-10 ms latency. As predictive maintenance checks extend from heavy machinery to medical wearables, the edge analytics market gains a larger operational footprint and becomes an indispensable layer in enterprise data strategy.

Demand for ultra-low-latency analytics

Autonomous robots, tele-surgery rigs, and collision-avoidance systems need decisions within 5 ms, a target unattainable when packets traverse distant clouds. Edge analytics eliminates the 50-150 ms round-trip and lowers the risk of mission-critical failures. Manufacturers that moved defect-detection algorithms from regional data centers to on-site nodes report double-digit yield improvements, reinforcing the business case for distributed intelligence.

Persistent data-security & sovereignty risks

Each edge gateway introduces an attack surface that adversaries can exploit through physical access or unpatched firmware. Finance and healthcare operators must also align with location-based data residency mandates, prompting adoption of trusted execution environments and zero-trust overlays that encrypt traffic end-to-end.

Other drivers and restraints analyzed in the detailed report include:

1. Rapid 5G roll-out unlocking edge use-cases
2. Cloud-native toolchains simplifying edge deployments
3. Integration complexity with brownfield OT systems

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Prescriptive engines are the fastest-advancing layer in the edge analytics market, growing at a 25% CAGR. They add decision automation to basic descriptive visibility, recommending the next best action once anomalies are detected. In 2024, descriptive modules still held 39% of revenue, but user demand has clearly pivoted toward higher-order insights that lift output and minimize risk. Edge devices now host compact reinforcement-learning agents that optimize robotics pathing on the fly, illustrating the commercial pull behind the transition.

Predictive algorithms remain a bridge between current dashboards and full automation. They enable forecast maintenance windows and inventory needs by correlating temperature spikes or traffic surges. Diagnostic analytics, though smaller, supplies root-cause clarity that prevents recurrence. Together these stacks help vendors package tiered offerings, embedding descriptive dashboards as entry points and layering prescriptive add-ons for premium subscribers. In turn, the edge analytics industry continues to mature toward outcome-based contracting.

On-premises nodes accounted for 56% of the edge analytics market size in 2024. They remain the first choice for data-sensitive sectors that cannot export personally identifiable or national-security information. Hospital networks, for instance, maintain imaging servers in-house so radiologists access scans without traversing external links. However, cloud-managed edges are scaling quicker, charting a 27.5% CAGR to 2030 as providers launch regional zones that meet residency rules.

Hybrid topology is emerging as the long-term norm. Sensitive workloads infer locally while batch trend analytics run in centralized clouds overnight. Central consoles push container updates, harmonize policy, and collect aggregated insights for executive dashboards, thereby delivering control without sacrificing agility. The arrangement reduces infrastructure duplication and keeps compute near data origin, aligning with both budget and compliance targets.

The Edge Analytics Market Report Segments the Industry Into by Deployment Type (On-Premises, and Cloud), Component (Solutions, and Services), Technology (Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics), End User Industry (BFSI, IT and Telecommunication, Manufacturing, Healthcare, Retail, and Others), and Geography.

Geography Analysis

North America retained leadership with 43% revenue in 2024 thanks to a mature hyperscale data-center footprint and early 5G monetization strategies. Telcos widened coverage to secondary metros, letting retailers place micro-data centers closer to suburban stores. Government incentives encouraged manufacturers to adopt smart-factory programs, embedding AI-driven process control at the line edge. Privacy rulings remain receptive to innovation provided encryption and audit trails meet industry norms. Policy clarity shortens procurement cycles and underpins steady demand across healthcare, retail, and energy domains.

Asia Pacific is the fastest-growing territory, forecast to log a 27% CAGR during 2025-2030. China scales provincial edge facilities that ingest sensor feeds from smart traffic lights and industrial robotics. Japan's automotive majors deploy predictive quality loops that slice rework costs, while India's mobile operators leverage new spectrum to launch private 5G campuses for logistics parks. Diverse regulatory positions on cross-border data flows push multinationals toward localized deployments, often using open-source stacks to avoid vendor lock-in. Investments in domestic semiconductor fabs further support a self-sustaining regional supply chain and embed resilience into edge projects.

Europe shows robust but measured uptake, guided by GDPR and proposed AI liability laws. Germany pioneers Industrie 4.0 projects that retrofit heritage plants with OPC UA gateways and containerized inference, balancing innovation with risk governance. France leads smart-transport pilots where real-time video analytics on roadside units improve public-safety response times. Nordic operators prioritize green hydrogen-powered edge sites to respect ESG mandates. Standard-setting bodies collaborate on secure boot, remote attestation, and data-exchange frameworks, fostering an interoperability ethos that benefits the wider edge analytics market.

1. Cisco Systems Inc.
2. IBM Corporation
3. Microsoft Corporation
4. Apigee Corporation
5. Dell Technologies Inc.
6. Intel Corporation
7. Oracle Corporation
8. SAS Institute Inc.
9. Amazon Web Services Inc.
10. Google Cloud Platform
11. Hewlett Packard Enterprise
12. Schneider Electric SE
13. Huawei Technologies Co.
14. SAP SE
15. Siemens AG
16. GE Digital
17. Foghorn Systems
18. Edge Impulse Inc.
19. Greenwave Systems
20. Predixion Software
21. AGT International Inc.

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 LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Proliferation of IoT end-points
  • 4.2.2 Demand for ultra-low-latency analytics
  • 4.2.3 Rapid 5G roll-out unlocking edge use-cases
  • 4.2.4 Cloud-native toolchains simplifying edge deployments
  • 4.2.5 On-device federated learning enhancing data privacy
  • 4.2.6 Liquid-cooling micro-data-centres enabling thermal-dense AI
• 4.3 Market Restraints
  • 4.3.1 Persistent data-security & sovereignty risks
  • 4.3.2 Integration complexity with brownfield OT systems
  • 4.3.3 Scarcity of tiny-ML / edge-AI engineering talent
  • 4.3.4 ESG-driven power-cap caps on distributed compute nodes
• 4.4 Evaluation of Critical Regulatory Framework
• 4.5 Value Chain Analysis
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Competitive Rivalry
• 4.8 Impact Assessment of Key Stakeholders
• 4.9 Key Use Cases and Case Studies
• 4.10 Impact on Macroeconomic Factors of the Market
• 4.11 Investment Analysis

5 MARKET SEGMENTATION

• 5.1 By Deployment Type
  • 5.1.1 On-Premises
  • 5.1.2 Cloud
• 5.2 By Component
  • 5.2.1 Solutions
  • 5.2.2 Services
• 5.3 By End-User Industry
  • 5.3.1 BFSI
  • 5.3.2 IT & Telecommunication
  • 5.3.3 Manufacturing
  • 5.3.4 Healthcare
  • 5.3.5 Retail
  • 5.3.6 Others
• 5.4 By Technology
  • 5.4.1 Descriptive Analytics
  • 5.4.2 Diagnostic Analytics
  • 5.4.3 Predictive Analytics
  • 5.4.4 Prescriptive Analytics
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 United Kingdom
    • 5.5.3.2 Germany
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Nordics
    • 5.5.3.7 Rest of Europe
  • 5.5.4 Middle East and Africa
    • 5.5.4.1 Middle East
    • 5.5.4.1.1 Saudi Arabia
    • 5.5.4.1.2 United Arab Emirates
    • 5.5.4.1.3 Turkey
    • 5.5.4.1.4 Rest of Middle East
    • 5.5.4.2 Africa
    • 5.5.4.2.1 South Africa
    • 5.5.4.2.2 Egypt
    • 5.5.4.2.3 Nigeria
    • 5.5.4.2.4 Rest of Africa
  • 5.5.5 Asia-Pacific
    • 5.5.5.1 China
    • 5.5.5.2 India
    • 5.5.5.3 Japan
    • 5.5.5.4 South Korea
    • 5.5.5.5 ASEAN
    • 5.5.5.6 Australia
    • 5.5.5.7 New Zealand
    • 5.5.5.8 Rest of Asia-Pacific

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
  • 6.4.1 Cisco Systems Inc.
  • 6.4.2 IBM Corporation
  • 6.4.3 Microsoft Corporation
  • 6.4.4 Apigee Corporation
  • 6.4.5 Dell Technologies Inc.
  • 6.4.6 Intel Corporation
  • 6.4.7 Oracle Corporation
  • 6.4.8 SAS Institute Inc.
  • 6.4.9 Amazon Web Services Inc.
  • 6.4.10 Google Cloud Platform
  • 6.4.11 Hewlett Packard Enterprise
  • 6.4.12 Schneider Electric SE
  • 6.4.13 Huawei Technologies Co.
  • 6.4.14 SAP SE
  • 6.4.15 Siemens AG
  • 6.4.16 GE Digital
  • 6.4.17 Foghorn Systems
  • 6.4.18 Edge Impulse Inc.
  • 6.4.19 Greenwave Systems
  • 6.4.20 Predixion Software
  • 6.4.21 AGT International Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-need Assessment