When it comes to face search and facial recognition technology, two very different types of solutions exist: turnkey consumer products like facesearching and enterprise cloud APIs like Amazon Web Services (AWS) Rekognition. While both can identify faces in images, they serve entirely different audiences, require different levels of technical expertise, and are built for different use cases. facesearching is a ready-to-use reverse face search engine that lets anyone upload a photo and find matching faces across the web. AWS Rekognition is a cloud-based API service that developers integrate into their own applications to add facial analysis and recognition capabilities. This comparison breaks down the key differences to help you choose the right solution for your needs. For more enterprise comparisons, see our guide on facesearching vs Microsoft Azure Face API.
What Is facesearching?
facesearching is a reverse face search engine designed for end users who want to find someone by photo, verify identities, or detect fake profiles. It is a complete, self-contained product: you visit the website, upload a photo, and within seconds receive results showing where that face appears across the web — including social media profiles, news articles, and other publicly indexed sources. No coding, no API integration, and no technical expertise required. The service is built for consumers, small businesses, journalists, HR professionals, and anyone who needs to verify an identity or find someone by photo. Photos are deleted immediately after each search, and the results come from publicly accessible sources. This makes facesearching an ideal tool for day-to-day identity verification tasks without the overhead of building or integrating a custom solution.
What Is AWS Rekognition?
AWS Rekognition is a cloud-based image and video analysis service from Amazon Web Services. It provides APIs that developers can use to add facial recognition, object detection, text extraction, content moderation, and other visual analysis capabilities to their own applications. Unlike facesearching, which is a ready-to-use product, AWS Rekognition is a set of building blocks. To use it, you need to be a developer (or hire one) who can write code to call the API, handle the responses, and build the user interface and workflow around it. AWS Rekognition can detect faces, compare faces, and search for faces within a collection that you create and manage — but it does not search the public web for matching faces. The face search capability is limited to the private collections you have built, making it fundamentally different from a reverse face search engine like facesearching that searches public web sources.
Key Differences at a Glance
The fundamental difference between facesearching and AWS Rekognition is the use case. facesearching is a reverse face search engine that searches the public web to find where a face appears online. It is designed for identity verification, fraud detection, and finding people. AWS Rekognition is a facial analysis API that developers use to build custom applications — it can detect if a face is present, analyze facial attributes, compare two faces, or search a private collection, but it does not search the internet. Another critical difference is the target user. facesearching is for anyone — no technical skills required. AWS Rekognition is for developers and organizations with engineering resources. Pricing models also differ: facesearching has simple, transparent consumer pricing, while AWS Rekognition charges per API call with complex usage-based pricing that can be difficult to predict. For a broader comparison of face search tools, see our guide on facesearching vs Clearview AI.
Choosing between facesearching and AWS Rekognition is not about which is better — it is about whether you need a ready-to-use face search engine or a developer toolkit for building custom facial recognition into your own application.
Use Case Comparison
- Identity verification: facesearching is purpose-built for this. Upload a photo and instantly see where that face appears online. AWS Rekognition can compare two faces but cannot search the web.
- Finding someone by photo: Only facesearching can do this. AWS Rekognition has no web search capability — it can only search faces within a collection you manually populate.
- Detecting fake profiles: facesearching can reveal if a profile photo is stolen or used across multiple fake accounts. AWS Rekognition cannot detect this on its own.
- Building a custom app: AWS Rekognition is the right choice here. If you need to add facial recognition features to your own application, its API provides the building blocks.
- Photo moderation: AWS Rekognition offers content moderation APIs that can detect inappropriate content. facesearching focuses on face matching and identity verification.
- Enterprise workflow integration: Both can serve enterprises, but in different ways. facesearching offers team plans and API access, while AWS Rekognition is inherently an API-first service.
Pricing Comparison
facesearching offers straightforward consumer pricing with a free tier for previewing results and paid plans for additional searches and features. The pricing is transparent, predictable, and designed for individuals and businesses of all sizes. AWS Rekognition uses a pay-per-use pricing model based on the number of API calls, the type of analysis performed, and the amount of data processed. While this can be cost-effective for high-volume applications, costs can be difficult to predict and can scale quickly. Additionally, AWS Rekognition requires you to factor in the cost of development, infrastructure, and ongoing maintenance — costs that are completely avoided with a ready-to-use solution like facesearching. For most individuals and small to medium businesses, the total cost of ownership for facesearching is significantly lower than building and maintaining a custom solution on AWS Rekognition.
Privacy and Data Handling
Both services take privacy seriously, but their approaches differ based on their architecture. facesearching deletes uploaded photos immediately after each search and never stores or adds them to any database. AWS Rekognition processes images and videos that you send to its API, and by default does not store them — but you can configure it to store images in your own face collections. AWS provides granular control over data storage, encryption, and retention policies through its cloud infrastructure. However, this also means you bear the responsibility for configuring and managing these privacy controls correctly. facesearching handles privacy automatically, with no configuration required from the user. For organizations with strict compliance requirements, AWS Rekognition's configurable data handling may be preferable, but it requires significant expertise to manage properly.
Which Solution Is Right for You?
If you are an individual, a small business owner, a journalist, an HR professional, or anyone who needs to verify identities and find people by photo — choose facesearching. It works immediately, requires no technical skills, searches the actual web for matching faces, and costs a fraction of what you would spend building and maintaining a custom solution. If you are a developer building a custom application that needs facial recognition capabilities — such as a photo management app, a security system, or a content moderation platform — AWS Rekognition provides the API building blocks you need. Just remember that it does not search the web for faces, so if your use case involves finding someone's online presence, you will need facesearching for that functionality. Many organizations use both: facesearching for day-to-day identity verification and AWS Rekognition for custom application features. Ready to get started with face search? Try facesearching free now.