Pathway vs Spider Cloud

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionPathwaySpider Cloud
Best ForReal-time streaming ETL and RAG pipelinesAI agents needing real-time web data for RAG
Core EngineRust-based streaming data processing engineRust-based crawling & scraping API
AI CapabilitiesLLM pack for RAG; BDH model is waitlist-onlyAI Studio (natural language crawling), Browser AI commands, Silk AI model
DeploymentSelf-hosted only (no managed cloud)Cloud API + self-host open source fallback
IntegrationsKafka, PostgreSQL, S3, Delta Lake, etc.LangChain, LlamaIndex, S3, GCS, Supabase, etc.

If you need live web data for AI agents (crawl, scrape, extract), Spider Cloud is the pick — real-time crawling with 99.9% success, AI Studio, and Browser AI commands. If your focus is on streaming ETL and live data pipelines (like Kafka to vector DB), Pathway’s Rust engine and incremental computation shine — but it requires self-hosting. Most AI builders will find Spider Cloud more immediately useful for grounding LLMs.

Try PathwayTry Spider Cloud
Pathway
Pathway

Pathway is a self-hosted Rust streaming engine for real-time AI pipelines, running the same Python or SQL code on live streams and batch

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Spider Cloud
Spider Cloud

Spider Cloud is a web scraping, crawling, and search API that streams live pages as markdown or JSON for AI agents and RAG pipelines.

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Pricing
Freemium
Freemium
Plans
$0/mo
Free plus license key
Custom
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
9 views
7.5k views
Skill Level
Advanced
Intermediate
API Available
Platforms
APIDesktop
WebAPIPluginCLIDesktop
Categories
📊 Data & Analytics⚙️ Developer Infrastructure
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
True streaming data processing engine written in Rust for real-time AI pipelines
Same engine and same code logic for streaming and batch backfill workloads
Incremental stream and table operations: join, filter, group-by, reduce
Advanced join types, temporal joins, windows, and ranges
Custom stateful reducers plus incremental apply and map-reduce
Async data processing that calls APIs, external libraries, and LLM services inside a dataflow
Built-in advanced indexing: vector search with HNSW, BM24, and hybrid modes
Custom indexing with knowledge graph and summarization techniques
LLM extension pack and unstructured data parsing toolkit for source sync, parsing, extraction, indexing
REST API endpoint serving query/answer and real-time features with sub-millisecond latency
Python Table API and SQL programming APIs
Develop and run pipelines in Jupyter notebooks, including in streaming on live data sources
Predefined API connectors to 300+ data sources plus a custom Python connector
AI toolkits for time-series operations, sampling, filters, classification, and clustering
Monitoring and traces via OpenTelemetry with Grafana integration
Scrape a single page into markdown, JSON, HTML, raw, or plain text
Crawl entire sites with each page streamed as one JSONL line in order as it finishes
Web search endpoint returns SERP results plus the scraped pages behind them
Custom browser renders like a user: scripts run, lazy images load, infinite scroll reaches the end
Load protected pages through a real browser engine with geo checks, returning a 200
Run full browser sessions over WebSocket with anti-detection and rotating exits
Send AI commands (Act, Extract, Observe) over the Browser API WebSocket
Send a prompt on a scrape or crawl request and get named fields back as JSON
Two-phase AI extraction: a fast model for most pages, a stronger model for complex layouts
Provider router sends scrape and crawl requests to outside providers on your own keys
Data connectors pipe crawl results into S3, GCS, Google Sheets, Azure Blob, or Supabase
Proxy network with 215M+ residential and ISP exits in 199 countries, rotated per request
MCP server at mcp.spider.cloud for Claude Code, Codex, Cursor, and Claude Desktop
1,000+ ready-made scraper examples across 32 categories, each with working code
API responses support JSON, JSONL, CSV, and XML; up to 10,000 core API requests per minute by default
Integrations
Kafka
PostgreSQL
Redpanda
Logstash
Slack
Google PubSub
S3
File System
JSON Lines
BigQuery
Delta Lake
Iceberg
Elasticsearch
QuestDB
LangChain
LlamaIndex
CrewAI
FlowiseAI
Langflow
Dify
Agno
MCP
Claude Code
Codex
Cursor
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

Who should pick which

  • AI agent developer
    Pick: Spider Cloud

    Needs real-time web data for LLM grounding; Spider Cloud's scraping API, AI Studio, and Browser AI commands provide turnkey data extraction.

  • Data engineer building streaming ETL
    Pick: Pathway

    Pathway's Rust engine handles incremental joins, windowed aggregations, and Kafka connectors — ideal for live data pipelines.

  • RAG pipeline builder
    Pick: Spider Cloud

    Spider Cloud directly outputs markdown/JSON for immediate ingestion into vector DBs; Pathway requires extra work to ingest from web APIs.

  • Team needing managed infrastructure
    Pick: Spider Cloud

    Pathway is self-hosted only; Spider Cloud offers a cloud API with no DevOps overhead.

Frequently Asked Questions

Pathway vs Spider Cloud: which should you choose?

If you need live web data for AI agents (crawl, scrape, extract), Spider Cloud is the pick — real-time crawling with 99.9% success, AI Studio, and Browser AI commands. If your focus is on streaming ETL and live data pipelines (like Kafka to vector DB), Pathway’s Rust engine and incremental computation shine — but it requires self-hosting. Most AI builders will find Spider Cloud more immediately useful for grounding LLMs.

Can I use Spider Cloud for real-time streaming data?

Spider Cloud is a request-response API for crawling/scraping; it does not natively process streams like Kafka. Use Pathway for that.

Does Pathway offer a cloud-hosted version?

No, Pathway is self-hosted only. You must manage your own infrastructure.

Which tool is better for RAG with live web content?

Spider Cloud excels at crawling and extracting live web data as markdown/JSON, perfect for RAG ingestion. Pathway can then process those streams if you build a pipeline, but it's not designed for initial data acquisition.

How do the pricing models compare?

Spider Cloud: usage-based (~$0.03/1k pages) + optional AI Studio. Pathway: free open-core (self-host), pay for your own compute.

Can I use Spider Cloud's Browser AI commands with Pathway?

Browser AI commands are Spider Cloud-specific. Pathway doesn't have browser automation.

Is Pathway's BDH model available for use?

No, the BDH model is currently waitlist-only. The only production-ready product is the streaming data framework.

Which tool integrates with LangChain?

Spider Cloud has direct integrations with LangChain, LlamaIndex, CrewAI, etc. Pathway does not list those integrations.

Which tool is open source?

Both have open-source cores: Spider Cloud's core is on GitHub; Pathway's entire data framework is open-core.

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Explore each tool further

Pathway
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Spider Cloud
View Spider Cloud reviewSpider Cloud alternatives

Browse these categories

Best AI Data & Analytics toolsBest AI Web Scraping & Search APIs toolsBest AI Developer Infrastructure toolsBest AI Browser & Computer-Use Agents tools
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Last reviewed: July 3, 2026