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The Mobile Backend as a Service (mBaaS) and low-code/no-code industry is experiencing rapid growth, driven by increasing demand for faster application development and digital transformation. It empowers both professional developers and citizen developers to build scalable applications with reduced time and cost. The market is competitive, with innovation focusing on AI integrations, broader platform capabilities, and user-friendly visual development tools.
Total Assets Under Management (AUM)
Low-Code Development Platform Market Size in United States
~US$10.3 billion (2023)
(24.6% CAGR)
- Increased demand for rapid application development.
- Growing adoption by enterprises for digital transformation.
- Expansion of citizen developer initiatives across industries.
10.3 billion USD
Generative AI will enable developers and non-developers to create applications, code snippets, and user interfaces from natural language prompts, accelerating development cycles significantly.
Integrating edge computing capabilities will allow mBaaS platforms to process data closer to the source, reducing latency and enabling more responsive real-time applications, especially for IoT and mobile use cases.
The rise of decentralized backend services and blockchain integration will offer enhanced security, data immutability, and new monetization models for applications, particularly in Web3 and FinTech.
The ADPPA is a proposed comprehensive federal privacy law in the US aiming to establish national standards for data privacy, including data minimization, consumer rights, and enforcement mechanisms.
This policy will mandate stricter data handling practices for Backendless, particularly concerning user data, requiring robust compliance features and potentially impacting data storage and processing strategies to align with federal standards.
Published by the White House Office of Science and Technology Policy, this framework outlines five principles for the design, use, and deployment of automated systems, emphasizing safety, equity, and transparency.
For Backendless's AI integrations, this framework will influence ethical AI development and deployment practices, particularly regarding data bias, algorithmic transparency, and user safety in features like AI-powered content generation or spam detection.
This voluntary framework provides a common language and systematic approach for managing cybersecurity risk, helping organizations understand, manage, and reduce their cybersecurity risks.
Backendless will likely adopt or align with this framework to enhance its platform's security posture, providing greater assurance to users regarding data protection and compliance, which is crucial for attracting enterprise clients.
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