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Edge computing is an IT architecture model where computing is performed at the edge of the network, near the source of data generation instead of transmitting the data to centralized processors located at remote data centers. Edge computing employs small servers and storage devices to process, collect and analyze real-time data close to the origination source. This helps deliver faster insights along with reduced latency and bandwidth requirements for transmission to cloud or centralized data centers. The technology finds widespread applications across a number of industries including automotive, manufacturing, healthcare and transportation.
The Edge Computing Market is estimated to be valued at US$ 111.3 Bn in 2023 and is expected to exhibit a CAGR of 15% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Dynamics:
Rising adoption of Internet of Things (IoT) technology across various industries is a key driver fueling growth of edge computing market. IoT is generating huge amount of data that needs to be processed in real-time to gain valuable insights. However, transmitting huge volumes of data to centralized cloud data centers for processing leads to increased latency and bandwidth issues. Edge computing addresses these challenges by providing processing capabilities closer to the IoT devices thereby enabling low latency applications for real-time analytics. Additionally, increasing deployment of 5G networking infrastructure capable of supporting ultra-low latency applications is also propelling the market growth. 5G when coupled with edge computing architecture provides enhanced connectivity and faster data transmission speeds necessary for mission critical applications like autonomous driving, telehealth, smart manufacturing and more.
Segment Analysis
The edge computing market is dominated by the hardware segment owing to increasing deployment of edge servers and devices by telecom operators and enterprises. Edge servers are witnessing high demand due to their capabilities to process data closer to the source of generation and deliver results in real-time.
PEST Analysis
Political: Government initiatives to develop smart infrastructure and 5G deployment are promoting edge computing adoption. However, data privacy and security laws pose challenges.
Economic: Edge computing helps organizations improve operational efficiency and reduce costs by processing data locally. The technology is positively impacted by the strong global economic growth.
Social: Increased mobile data usage and emergence of applications such as IoT and AI are major social drivers. Edge computing fulfills expectations of lower latency and seamless connectivity.
Technological: Technologies like 5G, IoT, AI and ML are driving the need for real-time processing of large data sets, thereby fueling the edge computing market. However, interoperability issues pose challenges.
Key players operating in the edge computing market include Microsoft Corporation, Google LLC, IBM Corporation, Huawei Technologies Co. Limited, and Cisco Systems Inc. The market has witnessed increased partnerships and collaborations among telecom operators and technology companies to develop edge computing infrastructure and solutions.
Regional analysis: North America dominates the global edge computing market owing to rapid technological advancements and presence of key players in the region. Asia Pacific exhibits the fastest growth in the edge computing market driven by rising IoT deployments, ongoing 5G trials and investments by telecom operators in various countries.
Key Takeaways
The global edge computing market is expected to witness high growth, exhibiting CAGR of 15% over the forecast period, due to increasing adoption of IoT devices globally. The proliferation of connected devices is resulting in generation of huge volumes of data that needs to be processed in real-time to derive meaningful insights, driving the need for edge computing.
*Note:
- Source: Coherent Market Insights, Public sources, Desk research
- We have leveraged AI tools to mine information and compile it
