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Publication: Sep 2024
Report Type: Niche Report
Report Format: PDF DataSheet
Report ID: CCT15855 
  Pages: 110+  

India Cloud Load Balancers Market Size and Forecast by Type, Deployment Model, Industry, Organization Size, Load Balancing Method, and Country: Statistics | 2019-2032

Report Format: PDF DataSheet |   Pages: 110+  

 Sep 2024  | 

India Cloud Load Balancers Market Growth and Performance

  • 2023 saw the India cloud load balancers market size rose to US$ 117.2 Million, marking a 18.5% YoY growth.
  • DataCube Research foresees, the cloud load balancers market in India is set to make significant strides on the global stage, with projected revenue reaching US$ 674.9 Million by 2032. Moreover, our analysis indicates a promising trajectory, an anticipated CAGR of 20.9% from 2024 to 2032.
  • Within the Indian cloud load balancers market, our research highlights the dominance of the global server load balancer (GSLB) segment, which claimed the largest market share of 57.5% in 2023. This underscores the segment's robust position and potential for continued growth.
  • In our projections, we also pay close attention to end user dynamics. We anticipate the healthcare sector to emerge as a key driver of growth, expanding with a fastest CAGR of 22.3% during the forecast period spanning 2024 to 2032.

India Cloud Load Balancers Market Scope

Analysis Period

2019-2032

Actual Data

2019-2023

Base Year

2024

Estimated Year

2024

CAGR Period

2024-2032
 

Research Scope

Type

Global Server Load Balancer (GSLB

Local Load Balancer (LLB

Deployment Model

Public Clou

Private Clou

Hybrid Clou

Industry

IT and Telecom

Media and Entertainment

Energy and Power

Transportation and Logistics

Healthcare

BFSI

Retail

Manufacturing

Public Sector

Other

Organization Size

Large Enterprise

Mid Enterprise

Small Enterprise

Load Balancing Method

Round Robi

Least Connection

IP Has

Weighted Round Robi

Least Response Tim


*Research Methodology: This report is based on DataCube’s proprietary 3-stage forecasting model, combining primary research, secondary data triangulation, and expert validation. [Learn more]