Zilliz Cloud Serverless 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

DimensionZilliz Cloud ServerlessSpider Cloud
Core FunctionVector database (managed Milvus)Web crawling & scraping API
Best ForGenAI apps needing scalable vector searchAI agents needing real-time web data for RAG
IntegrationsLangChain, LlamaIndex, OpenAI, Cohere, etc.LangChain, LlamaIndex, CrewAI, etc.
Unique FeatureTiered storage (DRAM/SSD/object) for cost savingsAI Studio + Browser AI commands (WebSocket)
Latest NewsLoon storage engine (2026-06-05); cost-aware VDBBench (2026-06-10)Browser AI commands (2026-03-05); scraper catalog (2026-02-25)

If your AI pipeline starts with fetching fresh web content, Spider Cloud is the leaner choice with an open-source core and pay-per-page pricing. If your priority is storing and searching vectors at scale for RAG, Zilliz Cloud Serverless offers auto-scaling and a generous free tier. They complement each other: use Spider to crawl, then feed embeddings into Zilliz.

Try Zilliz Cloud ServerlessTry Spider Cloud
Zilliz Cloud Serverless
Zilliz Cloud Serverless

Zilliz Cloud Serverless is a managed serverless vector database on Milvus, with auto-scaling compute and tiered storage for GenAI apps.

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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
From $0/month (Serverless); from $126/GB/month (Dedicated)
From $197/month (Dedicated)
Custom
Custom
$1/GB + $0.0001/CPU-min
From $6/mo
From $40/mo
Custom
Popularity
26 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
API
WebAPIPluginCLIDesktop
Categories
🗄️ Vector Databases & Retrieval
🌐 Web Scraping & Search APIs🖱️ Browser & Computer-Use Agents
Features
Auto-scaling serverless compute with no configuration required
Tiered storage across DRAM, SSD, and object storage
Hot/cold data separation keeps active vectors on fast disks
Hybrid search across dense and sparse vectors
Dense-text and multimodal hybrid query combinations
Similarity metrics: Cosine, Euclidean, inner product (IP)
Tunable consistency levels to trade accuracy against latency
Low-latency, high-recall vector search for real-time decisions
Loon storage engine for continuously changing vector data (June 2026)
On-demand compute for lake-scale indexing and search (May 2026)
Zero-copy access to external data without ingestion
Multimodal search over 3D assets via the Tripo integration (July 2026)
RESTful API plus Python, Java, Go, Rust, C++, and Node.js clients
One-click migration to dedicated clusters or self-hosted Milvus
System-managed index builds with pay-per-runtime job billing
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
LangChain
LlamaIndex
OpenAI
Cohere
Hugging Face
AWS SageMaker
Databricks
Terraform
Tripo
CrewAI
FlowiseAI
Langflow
Dify
Agno
MCP
Claude Code
Codex
Cursor
Claude Desktop
Amazon S3
Google Cloud Storage
Google Sheets

What real users say: Zilliz Cloud Serverless 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.

Zilliz Cloud Serverless

16 mentions across 1 sources · 95% positive (averaged across 1 source)

Product Hunt

What users praise

  • • Auto-scaling eliminates manual capacity planning for vector workloads.
  • • Tiered storage (DRAM/SSD/object) cuts costs up to 50x vs in-memory.
  • • Built on mature open-source Milvus with strong community trust.
  • • Free tier offers 5 GB storage and 2.5M vCUs per month.

What frustrates them

  • • Limited community reviews beyond Product Hunt launch day.
  • • Potential for unexpected costs with serverless auto-scaling at scale.
  • • No dedicated support on free tier; enterprise support unverified.
  • • Tiered storage latency may spike when data moves between tiers.

Researched Jul 3, 2026

Spider Cloud

No verifiable community signal. We scanned public discussion on Oct 14, 2026 and found posts matching the name “Spider Cloud”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

Who should pick which

  • Solo founder building a RAG chatbot with web data
    Pick: Spider Cloud

    Spider Cloud's free tier and simple API make it easy to fetch current web content; its LangChain integration streamlines building the data pipeline.

  • Startup scaling a GenAI recommendation system
    Pick: Zilliz Cloud Serverless

    Zilliz's auto-scaling and tiered storage keep costs low as data grows; the generous free tier allows prototyping without upfront cost.

  • Data scientist exploring similarity search on a budget
    Pick: Zilliz Cloud Serverless

    The free tier provides 5GB storage and 2.5M vCU, more than enough for experiments; hybrid search supports experimental use cases.

  • Team needing to scrape thousands of sites with AI extraction
    Pick: Spider Cloud

    Spider's AI Studio and Browser AI commands automate complex extractions; the scraper catalog provides ready-to-use examples.

  • Developer prototyping a multimodal RAG app
    Pick: Zilliz Cloud Serverless

    Zilliz supports dense, sparse, and multimodal vectors; integrates with Tripo for 3D assets and various embedding APIs.

Frequently Asked Questions

Zilliz Cloud Serverless vs Spider Cloud: which should you choose?

If your AI pipeline starts with fetching fresh web content, Spider Cloud is the leaner choice with an open-source core and pay-per-page pricing. If your priority is storing and searching vectors at scale for RAG, Zilliz Cloud Serverless offers auto-scaling and a generous free tier. They complement each other: use Spider to crawl, then feed embeddings into Zilliz.

Can I use Spider Cloud and Zilliz Cloud together?

Yes. Use Spider Cloud to crawl and extract content from the web, then generate embeddings and store them in Zilliz Cloud Serverless for vector search. Both integrate with LangChain and LlamaIndex.

Which has a more generous free tier?

Zilliz Cloud Serverless offers 5 GB storage and 2.5M vCU free per month, which can handle thousands of vectors. Spider Cloud's free tier is 500 pages per month, sufficient for small projects.

Does Spider Cloud support real-time streaming?

Yes. Spider Cloud's Browser AI commands via WebSocket allow real-time interaction (Act, Extract, Observe). It also supports streaming via its data connectors to cloud storage.

Does Zilliz support hybrid search?

Yes. Zilliz Cloud Serverless supports dense, sparse, and multimodal hybrid search, combining different vector types in a single query.

Which tool is better for RAG pipelines?

Both. Spider Cloud is ideal for the 'fetch' step (crawling and extracting web data), while Zilliz Cloud Serverless is ideal for the 'retrieve' step (storing and searching embeddings). They complement each other.

How does pricing scale for high volume?

Spider Cloud charges per page ($0.03 per 1000 pages on average). Zilliz charges per vCU-hour for compute and per GB for storage. For very large volumes, Zilliz's tiered storage can reduce costs.

Does Spider Cloud have an open-source option?

Yes. Spider Cloud has an open-source core available on GitHub, allowing self-hosting. Zilliz Cloud is proprietary but based on open-source Milvus.

What are the latest major updates?

Spider Cloud recently added Browser AI commands (2026-03-05) and a scraper catalog (2026-02-25). Zilliz Cloud Serverless introduced the Loon storage engine (2026-06-05) and cost-aware benchmarking via VDBBench (2026-06-10).

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Explore each tool further

Zilliz Cloud Serverless
View Zilliz Cloud Serverless reviewZilliz Cloud Serverless alternatives
Spider Cloud
View Spider Cloud reviewSpider Cloud alternatives

Browse these categories

Best AI Vector Databases & Retrieval toolsBest AI Web Scraping & Search APIs toolsBest AI Browser & Computer-Use Agents tools
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Last reviewed: July 3, 2026