HasData VS cppq

• Sub-2s Median Latency
  Every API request completes in about 2.1 seconds on average, even under high load.
• 99.9% uptime SLA
  Stay online with highly reliable servers, automated failover, and 24/7 infrastructure monitoring.
• Up to 10M Requests/Hour
  Handle massive scraping operations with infrastructure built to support 10 million hourly API calls.
• 100M+ Proxies
  Access hundreds of millions rotating IPs for global coverage and unblockable data collection.
• JavaScript Rendering
  Extract content from dynamic, JavaScript-heavy websites without manual browser emulation.
• Auto-Retry & Failover
  Built-in error handling and retries ensure high success rates even under volatile network conditions.
• Clean Structured Output
  Deliver consistent, parsed JSON with metadata, images, text, listings, and links.
• Full Anti-Bot Protection
  Bypasses Cloudflare, Datadome, and Akamai automatically — no proxy rotation or browser setup required.
• Easy Integration
  Connect in minutes using clear API documentation, SDKs, and straightforward REST architecture.

• Lightweight C++ implementation
  cppq is written in modern C++ and designed to be a minimal, efficient task queue library, making it a good fit for performance-sensitive applications where the overhead of scripting language runtimes is undesirable.
• Redis-backed reliability
  Built on top of Redis as the message broker, cppq benefits from Redis's persistence, atomic operations, and wide adoption, giving the queue system durability and the ability to survive process restarts.
• Inspired by proven design (asynq)
  The library's architecture mirrors the popular Go asynq task queue, so it inherits a well-thought-out API design for task enqueueing, retries, and worker processing patterns that have already been validated in production systems.
• Native integration for C++ projects
  For teams already working in a C++ codebase, cppq allows adding background job processing without needing to introduce a separate service written in another language (like Go or Python), simplifying the technology stack.
• Open source and inspectable
  Being open source on GitHub, developers can review the source code, modify it for custom needs, and contribute improvements, which offers transparency not available with closed-source queueing solutions.

Possible disadvantages

• Limited maturity and battle-testing
  Compared to established task queue libraries like Sidekiq, Celery, or asynq itself, cppq is a newer and smaller project with less real-world production usage, which may translate into undiscovered bugs or edge cases.
• Smaller community and ecosystem
  Because it has far fewer users and contributors than mainstream task queue systems, finding community support, third-party tutorials, or pre-built integrations is more difficult.
• Documentation gaps
  As a smaller project, cppq may have less comprehensive documentation compared to major task queue frameworks, requiring developers to read source code directly to understand advanced features or edge-case behaviors.
• C++ build and dependency complexity
  Using cppq requires managing C++ build toolchains and dependencies (such as a Redis client library), which can be more cumbersome than installing a package via pip or npm in other ecosystems.
• Fewer built-in features and tooling
  cppq likely lacks the extensive ecosystem tooling of more mature queues, such as web-based monitoring dashboards, extensive metrics/observability integrations, or advanced scheduling features found in more established solutions.