Sieve VS Cachely.dev

Compare Sieve VS Cachely.dev and see what are their differences

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Sieve

Easy sorting, filtering and pagination for .NET core

Cachely is a managed implementation of self-hosted remote cache for monorepos. Speed up CI, prove how much time and cost you saved, get build optimization suggestions, safe from cache poisoning (CVE-2025-36852). Turborepo and Bazel on the roadmap.

Landing page //
2022-11-02

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2026-08-20
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2026-08-20
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2026-08-20
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2026-08-20

Cachely is the managed self-hosted remote cache for Nx and Turborepo - the cache backend you'd otherwise build and run yourself, hosted for you on Cloudflare's edge (R2). It's a drop-in replacement for a DIY @nx/s3-cache / S3 bucket setup: point your build tool at Cachely with a token and two environment variables, and share build cache across CI and every developer's laptop.

Unlike a self-hosted cache, Cachely enforces read-only tokens at the API, so pull-request and fork builds can read but never write - closing the Nx cache-poisoning attack (CVE-2025-36852). It adds ROI reporting (the real build minutes and dollars the cache saved), per-tool insights, and build-optimization suggestions on top.

Pricing is a flat per-workspace subscription with no per-seat fees - add every developer, bot, and CI actor without watching the bill. Cachely never stores your source code; it caches only task outputs and their content hashes. Nx and Turborepo today; Bazel on the roadmap.

Sieve

Website: github.com
Pricing URL: -
$ Details
Release Date: -

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Cachely.dev

Website: cachely.dev
Pricing URL: Official Cachely.dev Pricing
$ Details: freemium
Release Date: 2026 June

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Sieve features and specs

Ease of Use
Sieve provides a straightforward and user-friendly interface for sorting and filtering data from API queries, making it accessible to developers with varying levels of experience.
Flexibility
The library is highly adaptable to different data structures and can be customized to fit specific application needs, offering a flexible approach to data handling.
Performance Optimization
Efficiently processes large datasets by minimizing unnecessary data queries, which can improve the performance of applications by speeding up data retrieval and processing times.
Community Support
Being an open-source project on GitHub, Sieve benefits from contributions and feedback from a community of developers, which can help improve the library over time.

Possible disadvantages of Sieve

Limited Documentation
The documentation for Sieve might not be as comprehensive as desired, potentially making it harder for new users to fully understand and utilize all of its features.
Complex Customization
While Sieve is flexible, implementing complex custom filters or advanced configurations may require a deeper understanding of its inner workings, which could be challenging for some developers.
Dependency Overhead
As with any third-party library, integrating Sieve into a project adds additional dependencies which may increase the maintenance burden and require regular updates.
Scalability in Large Applications
In very large applications with complex data relationships, Sieve's performance might degrade or not scale as efficiently compared to more robust, custom-built solutions.

Cachely.dev features and specs

Simplified Caching Setup
Cachely.dev likely offers an easy-to-integrate caching layer that reduces the complexity of manually configuring caching infrastructure, allowing developers to implement caching with minimal setup time.
Performance Improvement
By providing a dedicated caching solution, Cachely.dev can help reduce latency and improve application response times, especially for frequently accessed data or API responses.
Developer-Focused Design
The .dev domain and branding suggest the product is tailored specifically for developers, potentially offering clean APIs, SDKs, and documentation that fit into modern development workflows.
Scalability
As a specialized caching service, it may be built to handle scaling automatically, removing the burden of managing cache infrastructure as traffic grows.
Reduced Backend Load
Effective caching can significantly reduce the load on primary databases and backend services, potentially lowering infrastructure costs and improving overall system reliability.