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Storeradar.io VS cppq

Compare Storeradar.io VS cppq and see what are their differences

Storeradar.io

Download the entire Shopify store database as a single CSV. 2.5M stores, 1.9M emails, 190K phone numbers, full tech stack. One-time $149. No subscription.

Rating
0 reviews
Pricing
Paid Free trial $149 / One-off ("2.5M Shopify Stores", "1.9M emails", "190K phone numbers")
Alternatives Is it good?
cppq

Simple, reliable & efficient distributed task queue for C++

Rating
0 reviews
Alternatives Is it good?
Preferred Patron
Preferred Patron is the top Customer Loyalty Software Program for businesses in any industry of any size. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Base details

Website, pricing, platforms and company facts side by side.

Storeradar.io
cppq
Website storeradar.io github.com
Pricing
Paid Free trial $149 / One-off ("2.5M Shopify Stores", "1.9M emails", "190K phone numbers") Official pricing
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Company Startup from France · 1 - 9 employees · 2026 —
Listed in
Lead Generation Sales Intelligence Email Marketing Digital Marketing Sales Email Database B2B +4
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About Storeradar.io and cppq

In their own words, as submitted to SaaSHub.

Storeradar.io
cppq

StoreRadar is the complete Shopify store database, sold as a single downloadable CSV instead of a subscription. Most Shopify lead and tech-lookup tools charge every month for dashboard or API access. StoreRadar sells the data itself: one file, one payment, yours forever. What's in the file (2.5M...

Read more about Storeradar.io

No description of cppq yet.

Features and specs

What each product offers, as listed by its team.

Storeradar.io 3 features
cppq 5 features
  • Store discovery
    2.5M stores and 100-200 new ones daily
  • Stack detection
    app detection (250+ apps), Themes and technographics
  • Contact information
    Verified emails, phone numbers, Social media
  • 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.

Analysis

An editorial look at what each product does well and who it suits.

Storeradar.io
cppq

No analysis of Storeradar.io yet.

Overall verdict

  • cppq is a lightweight, Redis-backed distributed task queue for C++ inspired by Go's popular 'asynq' library. It's a good choice for developers who need a simple, dependency-light job queue system in C++ without the overhead of larger enterprise messaging systems, though it's a smaller, less battle-tested project compared to mature alternatives.

Why this product is good

  • Simple and lightweight design makes it easy to understand and integrate into existing C++ projects
  • Built on Redis, a well-established and reliable backend for queue storage, giving it a solid foundation
  • Inspired by asynq (a proven Go library), so the design patterns and task queue semantics are based on a well-thought-out model
  • Open source on GitHub, allowing developers to inspect, modify, and contribute to the code
  • Good fit for projects already using Redis, minimizing the need for additional infrastructure
  • Straightforward API for enqueueing and processing background jobs in C++ applications

Recommended for

  • C++ developers needing a background job/task queue without adopting a heavyweight message broker
  • Projects already using Redis as part of their infrastructure
  • Small to medium-sized applications requiring asynchronous task processing
  • Teams comfortable working with less mainstream or smaller open-source libraries and willing to contribute or debug issues themselves
  • Developers familiar with asynq (Go) looking for a similar pattern in C++
  • Prototyping or hobby projects where a minimal task queue solution is sufficient

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Storeradar.io
cppq
100% 100%
Lead Generation
0% 0%
100% 100%
Sales Intelligence
0% 0%
100% 100%
Sales
0% 0%
100% 100%
Email Database
0% 0%

Questions & Answers

As answered by people managing Storeradar.io and cppq.

Why should a person choose your product over its competitors?

Storeradar.io's answer

Tools like BuiltWith and Wappalyzer tell you the technology on a domain you already have. Seat-based databases like Apollo.io are priced for company sales teams. StoreRadar is different on both counts: it hands you every Shopify store up front, already enriched with contact data and tech stack, and it is priced as a one-time purchase from $149 rather than a monthly subscription. You get the complete, filterable dataset in one file, you own it, and there is no per-seat pricing or dashboard to learn. For anyone focused specifically on the Shopify ecosystem, it is the fastest and cheapest way to get the whole market in a spreadsheet.

What makes your product unique?

Storeradar.io's answer

StoreRadar sells the entire Shopify store database as a single downloadable CSV instead of a subscription. Most Shopify lead and tech-detection tools charge monthly for dashboard or API access; StoreRadar sells the data itself. One $149 payment gives you all 2.5M Shopify stores with 66+ columns per row, including 1.9M verified emails, phone numbers, installed apps, tech stack, and lead and SEO scores. You download it once and own the file forever, with no seats and no recurring fees.

How would you describe the primary audience of your product?

Storeradar.io's answer

StoreRadar is built for people who need Shopify store data once and want to own the file, not rent a dashboard. That includes Shopify agencies doing cold outreach and migration prospecting, app and theme developers looking for stores that run a particular app or stack, freelancers and solo marketers who need one campaign's worth of leads, and indie hackers validating Shopify-adjacent product ideas. The common thread is that they need the raw, filterable data rather than a seat-based sales-intelligence platform.

What's the story behind your product?

Storeradar.io's answer

StoreRadar started from a simple observation about lead databases: most people subscribe, export the data once, and cancel. The monthly dashboard, the seats, and the per-user pricing are built for large sales teams, not for the freelancer, the solo agency, or the single developer trying to find users for an app. So StoreRadar removed the SaaS wrapper and sells the export itself: the full Shopify store database as a one-time CSV. The insight was that people do not need another dashboard, they need the file.

Which are the primary technologies used for building your product?

Storeradar.io's answer

StoreRadar is a Ruby on Rails 8 application. It uses Hotwire (Turbo and Stimulus) for the interface, PostgreSQL as the primary database, and TailwindCSS for styling. On top of the app sits a continuous data pipeline that monitors the Shopify ecosystem and refreshes the store dataset daily. Payments run through Stripe.

Who are some of the biggest customers of your product?

Storeradar.io's answer

  • Independent Shopify agencies running client outreach
  • App and theme developers targeting Shopify merchants
  • Freelance marketers and cold-email consultants
  • Indie founders validating Shopify-adjacent product ideas

User comments

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