Edge computing vs. cloud computing: Key differences
Table of Contents
By: James M. Tobin, Edited by: Mitch Jacobson
Last updated: April 21, 2025
Edge computing and cloud computing are two of the most powerful data processing technologies currently available. Learn about their respective characteristics and compare their capabilities as you seek a deeper understanding of how these technologies work.
What is cloud computing?
Cloud computing uses scalable internet technology to deliver services and process and store data. People can access, use, and share cloud resources and data on demand and from any internet-connected location. These resources can include:
- Software
- Analytics tools
- Files
- Data and databases
The cloud offers cost advantages, price flexibility, security, and reliability. It can also save both time and computing resources. Given these advantages, cloud technologies are widely used by organizations of all sizes in both the public and private sectors.
Cloud computing: Capabilities and use cases
Organizations often use cloud solutions as an efficient, cost-effective alternative to internal technology deployments. Instead of making heavy investments in on-site technologies and services, organizations can outsource them to the cloud and use them as needed on a scalable basis.
Some of the major functionalities and use cases of cloud computing include:
- Infrastructure as a service (IaaS): IaaS delivers networking, computing, and data storage capabilities on demand, typically using a pay-as-you-go model.
- Software as a service (SaaS): Before the rise of cloud computing, organizations had to purchase and install software programs on individual machines in order to use them. SaaS changed this: It grants users access to applications and platform services over the internet, eliminating the need for physical software installations.
- Security as a service (SECaaS): SECaaS allows organizations to obtain cybersecurity services over the cloud instead of making costly investments in on-site data and network protection infrastructure.
Cloud computing uses a centralized model to manage and deliver these functionalities via a data center, usually through a single managed service provider.
Are there any drawbacks to cloud computing?
Cloud computing has several notable limitations and drawbacks. These include:
- Downtime: If cloud servers go offline, users cannot access cloud resources.
- Resource limitations: Despite excellent scalability, cloud resources are finite.
- Less user control: Cloud computing's centralized, outsourced nature requires users to relinquish resource and infrastructure management to end providers.
While cloud providers invest heavily in cybersecurity, cloud services also remain vulnerable to hacking and security threats.
What is edge computing?
Edge computing functions similarly to cloud computing, but with one important difference: Computing resources are situated closer to the end user's geographic location. This is where edge computing gets its name: it operates at the physical "edge" of the end user's devices or networks.
To deliver edge computing services, providers can use edge devices or software images. Edge devices use hardware to manage data transmissions across two network endpoints. Software images operate on servers, using snapshot-style data captures to facilitate the easy transmission or installation of application capabilities on remote machines.
Edge computing: Capabilities and use cases
Major applications of edge computing include:
- Artificial intelligence (AI): Edge resources are closer to their end users, enabling them to quickly process large quantities of data. This supports faster and more seamless AI performance, especially in AI models that rely on high accuracy or real-time functioning.
- Smart systems: Edge computing offers more efficient data handling and processing speeds, making it well-suited to internet-connected smart buildings and appliances that depend on rapid responses.
- Autonomous vehicles: Because traffic conditions are dynamic and constantly changing, edge computing's rapid processing capabilities make it ideal for managing the enormous quantities of data needed to operate self-driving vehicles.
- Healthcare: In medical emergencies, seconds can mean the difference between life and death. Edge computing's speed and efficiency make it a preferred technology in healthcare settings.
- Media streaming and content delivery: Edge computing makes streaming and the delivery of data-rich media smoother and more reliable.
Edge computing also has compelling use cases in site security, manufacturing, and retail, among other industries.
Are there any drawbacks to edge computing?
Shortcomings and disadvantages of edge computing technologies include:
- More attack surfaces: Edge computing often engages a large number of connected devices, creating more vectors for cyberattackers to exploit.
- Higher local hardware needs: Devices connected to edge systems require relatively sophisticated hardware to process and transmit data to edge networks.
Where edge computing and cloud computing overlap
Cloud computing and edge computing both offer:
- Outsourced and offsite computing resources and workload management
- Streamlined data analytics capabilities
- Cost-effective solutions to organizational resource limitations
- Application suites capable of running on any operating system
Providers can also combine cloud and edge services to take advantage of each technology's unique performance benefits. These solutions are known as "hybrid clouds."
Snapshot of edge computing vs. cloud computing
Cloud computing
- Centralized
- Resource deployments offer high levels of computing and data processing power.
- High latency: Data takes more time to travel across a cloud network.
- Slower data processing due to high latency.
- Compliance requirements are more complex due to data often traveling across jurisdictional and geographic boundaries.
- Less vulnerable to physical cyberattacks due to the presence of wide security perimeters.
Edge computing
- Decentralized
- Resource deployments save bandwidth but sacrifice some networking and processing capabilities.
- Low latency: Data takes less time to travel across an edge network.
- Faster data processing due to low latency.
- Compliance requirements are less complex since data remains physically proximate to its end users.
- More vulnerable to physical cyberattacks due to their larger attack surfaces.