Cody by Sourcegraph vs Tabnine

Detailed side-by-side comparison to help you choose the right tool

Cody by Sourcegraph

🔴Developer

AI Development Assistants

AI coding assistant powered by Sourcegraph's code intelligence platform, providing full codebase context awareness across repositories for chat, code completion, and agentic coding workflows.

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Starting Price

Free

Tabnine

🔴Developer

App Deployment

Privacy-focused AI code completion that runs locally or in your cloud — delivering intelligent suggestions across 30+ languages without exposing source code to external servers, built for regulated industries and security-conscious dev teams.

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Starting Price

Custom

Feature Comparison

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FeatureCody by SourcegraphTabnine
CategoryAI Development AssistantsApp Deployment
Pricing Plans8 tiers8 tiers
Starting PriceFree
Key Features
  • AI-powered code completion with codebase context
  • Natural language chat for code Q&A and generation
  • Auto-edit suggestions based on cursor and editing patterns
  • AI code completion across 30+ languages
  • On-premises and air-gapped deployment
  • Natural language to code generation

Cody by Sourcegraph - Pros & Cons

Pros

  • Deep codebase context via Sourcegraph's Code Search API, pulling relevant symbols and usage patterns across entire codebases for more accurate suggestions
  • Multi-LLM support lets users choose between Claude, GPT-4o, Gemini and other models, and enterprise customers can bring their own keys
  • Wide IDE coverage including VS Code, JetBrains, Visual Studio (experimental), a web interface in the Sourcegraph platform, and CLI access
  • Strong fit for large monorepos and polyrepo enterprise environments where cross-repository context is critical for accurate AI assistance
  • Customizable prompts and commands let teams encode standardized workflows (test generation, code review checklists, documentation) as reusable templates
  • Enterprise-grade governance with SSO, audit logs, repo permission-aware context, and guardrails for compliance-sensitive industries

Cons

  • Full enterprise context features require deploying and configuring Sourcegraph's code intelligence platform, which adds operational overhead
  • Free tier usage limits are more restrictive than some competitors like GitHub Copilot's free offering
  • Maximum value requires proper codebase indexing setup — context quality scales with indexing completeness
  • Smaller extension marketplace compared to GitHub Copilot's broader third-party integration ecosystem
  • Amp (the agentic evolution) is a separate product requiring additional onboarding and different workflows from the core Cody experience
  • Enterprise deployment complexity can be significant for smaller teams without dedicated DevOps resources
  • Learning curve to leverage advanced features like custom prompts, context filters, and @-mentions effectively

Tabnine - Pros & Cons

Pros

  • Only major AI coding assistant offering true on-premises and air-gapped deployment
  • SOC 2 Type II, GDPR, and ISO 9001 certified — strong compliance posture for regulated industries
  • IP indemnification and permissively-licensed training data eliminate copyright risk
  • Integrates into existing IDEs without forcing a new editor (unlike Cursor)
  • Codebase-wide personalization generates suggestions matching your team's actual patterns
  • Supports 30+ programming languages across all major IDE families
  • AI agents for code review and Jira ticket implementation on Enterprise tier

Cons

  • Completion quality trails tools powered by frontier models like GPT-4o or Claude
  • Enterprise pricing at $39/user/month is expensive for small teams or startups
  • Free tier is limited to basic completions with no chat or advanced agents
  • On-premises deployment requires dedicated infrastructure and IT resources to maintain
  • Codebase personalization only available on the Enterprise plan, not Dev
  • Smaller ecosystem of integrations compared to GitHub Copilot's deep Microsoft/GitHub ties

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