PgGraph vs Spider Cloud
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | PgGraph | Spider Cloud |
|---|---|---|
| Pricing | Free (open source, self-host) | Freemium (free tier, pay-as-you-go, AI Studio $6/mo) |
| Core Function | In-memory graph queries on existing Postgres data | Web crawling/scraping API for AI agents |
| Engine | Rust-based, lightweight index, no data movement | Rust-based, high-performance scraping engine |
| Integrations | PostgreSQL | LangChain, LlamaIndex, CrewAI, FlowiseAI, AutoGen, Agno, Dify, GCS, S3, Supabase |
| Best For | AI agents needing relational memory, fraud detection, permission checks | AI agents needing real-time web data for RAG and LLM context |
| Not For | Teams needing graph visualization UI or managed cloud | Simple one-off scrapes, projects requiring massive residential proxies |
PgGraph and Spider Cloud solve entirely different problems: PgGraph is a virtual graph layer for querying relationships in your existing Postgres without moving data, while Spider Cloud is a web scraping API for feeding real-time web data into AI agents. Choose PgGraph if you need graph queries on your own database; choose Spider Cloud if you need to extract and structure external web content.
AI web scraping API: crawl, scrape, search any site into markdown or JSON at 10k req/min.
Visit WebsiteWhat real users say: PgGraph vs Spider Cloud
Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.
PgGraph
2 mentions across 1 sources · 60% positive — mixed
Hacker News
What users praise
- • No data duplication or ETL needed—works directly on existing Postgres schemas.
- • Rust-based engine for low latency and concurrent access.
- • Sub-millisecond multi-hop queries on relationship indexes.
- • Lightweight memory usage (~34x less RAM than traditional graph DBs).
What frustrates them
- • Extremely limited community feedback and real-world deployment stories.
- • No support for standard graph query languages (Cypher, SPARQL, Gremlin).
- • Performance under heavy write loads or large graphs is unverified.
- • Documentation on failure recovery and schema changes is lacking.
Researched Jul 3, 2026
Spider Cloud
41 mentions across 2 sources · 0% positive — critical
YouTube, Lemmy
What users praise
- • Competitive pay-as-you-go pricing at $1/GB with no expiry.
- • Default rate limit of 10,000 requests per minute is generous.
- • Broad output formats (HTML, markdown, JSON, CSV) cover diverse needs.
- • Integrated Web Search API bundles SERP and extraction for AI agents.
What frustrates them
- • No community feedback to confirm reliability or performance.
- • Self-reported metrics lack independent verification.
- • Stealth browser success may vary across real sites.
- • Potential legal risks from scraping; compliance is user's responsibility.
Researched Aug 26, 2026
Who should pick which
- AI agent developer using PostgresPick: PgGraph
PgGraph provides agentic memory and multi-hop relationship queries directly on your existing Postgres schema without moving data, ideal for AI agents that need to reason about connected entities like users, orders, and permissions.
- RAG pipeline builderPick: Spider Cloud
Spider Cloud's web scraping API integrates with LangChain, LlamaIndex, and other RAG frameworks, supplying real-time web content as structured data for LLM context enrichment.
- Fraud detection team (fintech)Pick: PgGraph
PgGraph enables real-time multi-hop relationship traversal (e.g., linking accounts, devices, transactions) for fraud pattern detection, with 34x less RAM than traditional graph DBs.
- Developer needing web data for AI agentsPick: Spider Cloud
Spider Cloud's Browser AI commands and 1,000+ scraper examples allow quick extraction of structured web data via natural language or code, with anti-detection and stealth features.
- Platform engineer doing dependency mappingPick: PgGraph
PgGraph's dependency and blast radius analysis leverages Postgres foreign keys to map service dependencies without additional databases or migration.
Frequently Asked Questions
PgGraph vs Spider Cloud: which should you choose?
PgGraph and Spider Cloud solve entirely different problems: PgGraph is a virtual graph layer for querying relationships in your existing Postgres without moving data, while Spider Cloud is a web scraping API for feeding real-time web data into AI agents. Choose PgGraph if you need graph queries on your own database; choose Spider Cloud if you need to extract and structure external web content.
Can I use PgGraph with non-PostgreSQL databases?
No, PgGraph is specifically designed to create a virtual graph layer over PostgreSQL. It requires a Postgres source of truth and does not support other databases.
Does Spider Cloud offer a free tier?
Yes, Spider Cloud has a free tier with limited usage. It also offers pay-as-you-go pricing and an AI Studio add-on for $6/month.
Which tool is better for AI agents that need real-time web data?
Spider Cloud is specifically built for this purpose, with web crawling, scraping, and search APIs that integrate with AI agent frameworks like LangChain and CrewAI.
Can PgGraph replace a traditional graph database like Neo4j?
For use cases requiring graph queries over existing Postgres data without moving it, yes. But it lacks a dedicated storage engine, UI visualization, and is not a full graph database replacement.
Does Spider Cloud support JavaScript-rendered pages?
Yes, Spider Cloud's Browser Cloud provides stealth anti-detection and can render JavaScript. The Browser AI commands also allow interaction (click, type) with dynamic pages.
Is PgGraph open source?
Yes, PgGraph is open source with an API for integration. You can self-host it on your infrastructure.
How does PgGraph achieve low memory usage?
It creates an in-memory index of relationship keys (IDs, foreign keys) without copying row data, claiming 34x less RAM than traditional graph databases.
Does Spider Cloud offer data connectors?
Yes, as of February 2026, Spider Cloud added data connectors to pipe crawl results to S3, GCS, Google Sheets, Azure Blob, and Supabase.
More PgGraph or Spider Cloud comparisons
Choose Vercel if you need to deploy full-stack apps or AI agents with sandboxed execution, global CDN, and rich framework integrations. Choose Spider Cloud if your primary need is fast, reliable web s
If your stack lives inside Microsoft 365 and you need governed, interactive dashboards, Power BI is the natural choice with unmatched ecosystem integration. But if you're building AI agents or RAG pip
If you need to run LLMs locally for privacy and agentic workflows, LM Studio is the free, polished choice with recent updates like multi-GPU tensor parallelism and MTP speculative decoding. If your pr
Tableau and Spider Cloud serve entirely different purposes: Tableau is a full-featured BI platform for human analysts building interactive dashboards, while Spider Cloud is a purpose-built scraping AP
Spider Cloud and Amplitude solve entirely different problems. Choose Spider Cloud if you need high-volume, low-cost web data extraction for AI agents and RAG pipelines—it’s purpose-built for that. Cho
Choose Spider Cloud if you need a fast, low-cost web scraping API for feeding real-time data into AI agents and RAG pipelines. Choose Looker if you're an enterprise on Google Cloud needing governed, A
Explore each tool further
Browse these categories
One email a week — new tools, honest comparisons, no spam.
Last reviewed: July 3, 2026