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This guide will help you navigate CyborgDB’s documentation effectively and find the information you need quickly.

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Documentation Structure

Our documentation is organized into four main sections:

Introduction

Core concepts and getting started
  • Architecture and key concepts
  • Deployment models (Service vs Embedded)
  • Database integration options
  • Quickstart guides

CyborgDB Service

Self-deployed REST API service
  • REST API documentation
  • Client SDKs (Python, JS/TS, Go, C++)
  • Docker and Python deployment
  • Authentication and configuration

CyborgDB Embedded

Direct library integration
  • Python and C++ bindings
  • Installation and setup guides
  • Performance tuning
  • Advanced configuration

Integrations

Framework integrations
  • LangChain integration
  • Migration from other vector databases
  • Framework-specific guides
  • Custom integrations

Quick Access

  • Search (Ctrl/Cmd + K) - Find topics instantly
  • Table of Contents - Navigate within articles
  • Breadcrumbs - Track your location

Page Types

  • Quickstart Guides - Step-by-step tutorials
  • Conceptual Guides - How things work
  • Reference Docs - Complete API documentation
  • How-to Guides - Practical solutions

Code Examples

  • Multiple Languages - Python, JavaScript, TypeScript, C++
  • Copy Button - One-click code copying
  • Runnable Examples - Complete working code

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Conventions Used

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Code and Commands

# Terminal commands are shown in code blocks like this
pip install cyborgdb-core

# Python code examples use syntax highlighting
from cyborgdb_core import Client
client = Client(api_key="your-key")

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Information Callouts

Notes provide helpful context and additional information that’s good to know.
Tips share best practices and insider knowledge to help you succeed.
Warnings highlight important considerations that could affect your implementation.

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Finding What You Need

  • I'm new to CyborgDB
  • I want to get started quickly
  • I need specific information
  • I'm migrating from another database
First time learning about confidential vector search→ Start with About CyborgDB then try the Quickstart GuideGet oriented with core concepts and architecture before diving into implementation.

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Search Tips

  • Exact phrases: Use quotes for exact matches: "create index"
  • Multiple terms: Search for multiple concepts: python authentication
  • Method names: Search for specific functions: similarity_search

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Code Examples

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Language Tabs

Many code examples include multiple language options: 
from cyborgdb_core import Client
client = Client(api_key="your-key")

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Runnable Examples

Look for complete, runnable examples that you can copy and execute directly: 
# Complete working example
from cyborgdb_core import Client, DBConfig

client = Client(
    api_key="your-api-key",
    index_location=DBConfig("memory"),
    config_location=DBConfig("memory")
)

# Create index and add vectors
index = client.create_index("my-index", dimension=384)
index.add_vectors([1, 2, 3, ...], metadata={"doc": "example"})

# Search for similar vectors  
results = index.search([1, 2, 3, ...], k=5)
print(results)

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Getting Help

Contact Support

General inquiries and enterprise supportVisit our contact page for sales, partnerships, and enterprise support requests

Priority Support

Get faster support when logged inLog into the CyborgDB dashboard for priority support and account-specific help