# Apify vs Cognitora

Apify records 4,147,762 monthly visits with +3.9% month-over-month growth and Freemium, Contact for Pricing pricing. Cognitora records 0 monthly visits with — growth and Open Source pricing.

| Metric | [Apify](https://openaitools.app/tool/apify) | [Cognitora](https://openaitools.app/tool/cognitora) |
| :--- | :--- | :--- |
| Website URL | https://www.apify.com | https://cognitora.dev |
| Categories | AI Web Scraping, AI Agent, AI API, AI Developer Tools | AI Agent, AI API, AI Developer Tools |
| Pricing Model | Freemium, Contact for Pricing | Open Source |
| Monthly Visits | 4,147,762 | 0 |
| MoM Growth Rate | +3.9% | — |
| Primary Market | United States | Global |
| Direct Visits | 1,816,433 | 0 |
| Review Score | 4.6 | 4.6 |
| Saved Count | 6 | 0 |
| Supported Platforms | Website | Website |

## Apify

Apify started as a general-purpose web automation cloud and has grown into one of the largest marketplaces of turnkey web data extractors. The platform exposes a store of Actors — small containerized programs built by Apify and by third-party developers — that handle jobs like pulling Google Maps listings, TikTok videos, Instagram posts, Amazon prices, or crawling a documentation site into clean Markdown for a RAG pipeline. Each Actor runs on Apify's cloud, can be triggered from an API, scheduled on a recurring basis, and wired into downstream storage or applications.\n\nBecause running scrapers in production is mostly an infrastructure problem, Apify bundles the unglamorous parts: rotating residential and datacenter proxies, browser fingerprinting and anti-blocking, retry logic, dataset and key-value storage, and monitoring. Developers who would rather write their own code can build Actors with the Apify SDK in Python or JavaScript, or use Crawlee, Apify's open-source crawling and browser-automation library, which works with Playwright, Puppeteer, Selenium, and BeautifulSoup.\n\nRecently the platform has positioned itself around AI: the Apify MCP server and CLI let AI agents and assistants discover and call Actors as tools, and the Website Content Crawler Actor is explicitly designed to feed LLM applications and vector databases. Pricing follows a freemium model with monthly platform credits, pay-per-usage pricing for many Actors, and custom enterprise agreements.

**Pricing & Plans:** Freemium: a free plan with monthly usage credits, paid subscription tiers that scale credits and concurrency, consumption-based charges for many marketplace Actors, and custom enterprise pricing. Developer payouts are also available for published Actors.

- **Actor marketplace:** Over one hundred thousand ready-to-run scrapers and automation tools covering social media, maps, e-commerce, real estate, and general web crawling.
- **MCP server and CLI:** Connect Apify Actors directly to AI assistants and agents so they can search the store, run scrapers, and pull structured results as tool calls.
- **Anti-blocking and proxy infrastructure:** Managed proxy rotation and unblocking are built into the platform, so scrapers keep working when target sites add defenses.
- **Crawlee and the Apify SDK:** An open-source crawling library plus Python and JavaScript SDKs for building custom Actors with Playwright, Puppeteer, Selenium, or Cheerio.
- **Scheduling, storage, and integrations:** Recurring runs, dataset exports to CSV/JSON/Excel, webhooks, and integrations with LangChain, LlamaIndex, Zapier, and thousands of apps.

**Strengths:** Enormous library of maintained scrapers means many jobs need no code at all; Infrastructure concerns like proxies, retries, and blocking are handled for you; Agent-ready through MCP, CLI, and API, with LangChain and LlamaIndex integrations; Generous free tier for testing plus a developer revenue-share program

**Limitations:** Costs scale with usage, so high-volume scraping can get expensive quickly; Quality varies between community-built Actors and first-party ones; Target sites change frequently, so some Actors break or need updating over time

[Profile (Markdown)](https://openaitools.app/tool/apify.md)

## Cognitora

Cognitora is an open-source orchestration layer for distributed large language model inference, written in Rust. Rather than shipping a single inference engine, it joins the engines you already operate — vLLM, SGLang, llama.cpp, Apple MLX, a TRT-LLM spawn driver and its own preview cgn-infer engine — into one cluster behind a single OpenAI-compatible gateway. You can deploy it instead of an orchestrator such as NVIDIA Dynamo, and the project positions itself as supporting more engines, running on bare metal without Kubernetes, factoring power consumption into scheduling and avoiding a Python control plane.

Its core innovation is KV-aware routing. The router scores nodes by the longest-prefix overlap of sequence-chained BLAKE3 digests, using cache claims that agents report in heartbeats. In real llama.cpp runs the router reportedly added 0.9–2.0 ms at p50. Beyond routing, the platform splits prefill from decode across separate pools (handing KV cache off through NixlConnector), maintains a multi-tier RAM/SSD KV cache with cross-node QUIC fetch, and offers pluggable offload backends including nixl, lmcache, hicache and kvbm.

The stack is modular: cgn-router for routing, cgn-agent to supervise engines on each node, cgn-kvcached for tiered caching, cgn-metrics for Prometheus plus Redfish/NVML power telemetry, cgn-ctl as an admin CLI, an optional Kubernetes operator, and a preview native engine. Energy-aware scheduling drains hot nodes, a closed-loop autoscaler reacts to power readings, and gossip-based discovery removes the need for etcd. Security options include optional mTLS, SHA-256 checksummed releases and OIDC or scoped API-key auth. The project ships six static binaries for systemd installs, Helm charts for Kubernetes, and a single-file HTML cluster dashboard that visualises throughput, latency percentiles, KV utilisation and joules per token without Grafana.

**Pricing & Plans:** Cognitora is open source and installs from its repository; there is no published per-seat or per-token price. Deployment cost is your own hardware, so total spend depends on the GPUs and nodes you run.

- **KV-aware request routing:** Routes each request to the node whose cache holds the longest matching prompt prefix, using longest-prefix overlap of BLAKE3 sequence digests to avoid repeated prefill work.
- **Engine-agnostic gateway:** One OpenAI-compatible API in front of vLLM, SGLang, llama.cpp, Apple MLX and a TRT-LLM spawn driver, so you can mix engines inside a single cluster.
- **Prefill/decode disaggregation:** Runs prefill and decode on separate replica pools with KV handoff through NixlConnector, letting each phase use hardware suited to it.
- **Energy-aware scheduling:** Folds Redfish and NVML power readings into routing scores, applies soft per-node watt caps, and drains hot nodes automatically to cut energy per token.
- **Bare metal to Kubernetes:** Deploys as six static binaries under systemd without Kubernetes, or with an optional kube-rs operator exposing InferenceCluster, ModelPool and RoutingPolicy CRDs.

**Strengths:** Open source and self-hostable, with no per-token or per-seat licensing cost; KV-aware routing meaningfully reduces duplicated prefill work across a fleet; Works with many engines, so it does not lock you into one vendor's runtime; Runs on bare metal without Kubernetes, keeping the operational surface small

**Limitations:** Requires substantial LLM infrastructure knowledge and hands-on GPU hardware to evaluate; Several headline capabilities are on the main branch but not yet in a tagged release; TRT-LLM support is a spawn driver only, without a default recipe or CI GPU test

[Profile (Markdown)](https://openaitools.app/tool/cognitora.md)

## Frequently Asked Questions

### How do Apify and Cognitora compare in monthly traffic?

Apify has 4,147,762 monthly visits, while Cognitora has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Apify has a month-over-month growth rate of +3.9%; Cognitora has —.

### How does pricing compare?

Apify: Freemium, Contact for Pricing. Freemium: a free plan with monthly usage credits, paid subscription tiers that scale credits and concurrency, consumption-based charges for many marketplace Actors, and custom enterprise pricing. Developer payouts are also available for published Actors. Cognitora: Open Source. Cognitora is open source and installs from its repository; there is no published per-seat or per-token price. Deployment cost is your own hardware, so total spend depends on the GPUs and nodes you run.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 2 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | The AI developer cloud for GPU pods, serverless inference and clustering | [.md](https://openaitools.app/tool/runpod.md) |
| 3 | [Firecrawl](https://openaitools.app/tool/firecrawl-dev) | 1,828,239 | -1.9% | Freemium, Contact for Pricing | Provides direct LLM-ready markdown conversion via API, but lacks Apify's massive marketplace of pre-built scraping actors. | [.md](https://openaitools.app/tool/firecrawl-dev.md) |
| 4 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all b | [.md](https://openaitools.app/tool/together-ai.md) |
| 5 | [Clay](https://openaitools.app/tool/clay-2-0) | 1,267,465 | -2.7% | Freemium, Free Trial, Contact for Pricing | Build GTM systems that turn data into revenue | [.md](https://openaitools.app/tool/clay-2-0.md) |
| 6 | [Browser Use](https://openaitools.app/tool/browser-use) | 1,206,376 | +41.1% | Freemium, Paid, Contact for Pricing | Browser agents and stealth cloud browsers for real web tasks | [.md](https://openaitools.app/tool/browser-use.md) |
| 7 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Serverless cloud infrastructure for AI and data workloads | [.md](https://openaitools.app/tool/modal-com.md) |
| 8 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | An AI-native cloud built from silicon to API for training, tuning, and serving models | [.md](https://openaitools.app/tool/nebius.md) |
| 9 | [Bright Data](https://openaitools.app/tool/bright-data) | 802,752 | -5.9% | Free Trial, Paid | Offers enterprise-grade proxy networks and raw web data infrastructure, but lacks Apify's plug-and-play actor marketplace. | [.md](https://openaitools.app/tool/bright-data.md) |
| 10 | [Salad](https://openaitools.app/tool/salad-gpu-cloud) | 713,519 | +10.4% | Free Trial, Paid, Contact for Pricing | Distributed GPU cloud that orchestrates the world's idle consumer GPUs | [.md](https://openaitools.app/tool/salad-gpu-cloud.md) |

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Source: https://openaitools.app/compare/apify-vs-cognitora

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)