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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

775K visits/mo
Watsonx.data logo
Watsonx.data
✓ verifiedFree trial

IBM's open, hybrid data lakehouse that connects, governs and optimizes enterprise data to make it AI-ready across clouds and on-premises.

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K saves
Vespa logo
Vespa
✓ verifiedFree trial

Open-source AI search and vector database platform for building large-scale search, RAG, and recommendation systems.

Pricing

No public pricing

Unlocker API: Starts from $1.05/1k req
Crawl API: Starts from $1.05/1k req
SERP API: Starts from $1.05/1k req
Browser API: Starts from $5.88/GB
Scrapers: Starts from $300/mo
Datasets: Starts from $250/mo
Functions: Starts from $2.7/1k req
RetailInsights: Starts from $1,000/mo
Residential Proxies: Starts from $3.53/GB
Datacenter Proxies: Starts from $0.9/IP
ISP Proxies: Starts from $1.3/IP
Mobile Proxies: Starts from $5.88/GB
Custom Scraper: Starts from $300/mo

No public pricing

Free trial available

No public pricing

No public pricing

Free trial available

Core features
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Multi-engine support (Google, Duckduckgo, Bing, Yandex, Baidu)
  • Real-time structured SERP data
  • Pay-per-successful-request pricing
  • Full JavaScript support
  • Precise geo-location targeting
  • Structured data delivery in JSON or HTML
  • Open hybrid data lakehouse
  • Connects data across clouds and on-prem
  • Governance, lineage and access controls
  • Business-context enrichment
  • AI-ready data for analytics and models
  • Fast tensor operations
  • Differentiable tensors for gradient-based optimization
  • Network connectivity
  • Integration with Bun and Flashlight
  • Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
  • Combined vector, text, and structured search
  • Distributed machine-learned ranking at query time
  • Streaming search mode for cost-efficient personal/private data
  • Support for retrieval-augmented generation pipelines
  • Continuous deployment and automated scaling
  • Open-source core with a managed cloud option
Use cases
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Organic keyword tracking
  • Brand protection
  • Price comparison
  • Market research
  • Detect copyright infringements
  • Ad intelligence
  • Unifying fragmented enterprise data
  • Governing data for AI workloads
  • Moving AI pilots to production
  • Powering analytics with trusted data
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Building large-scale enterprise search engines
  • Powering RAG pipelines that need strong retrieval relevance
  • Building recommendation and ad-targeting systems
  • Search over personal/private data at lower indexing cost
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