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Merge pull request #33 from HelixDB/mintlify/geo-optimization-review-89215
GEO Optimization Complete
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docs.json

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}
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},
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"seo": {
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"indexing": "all",
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"metatags": {
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"description": "HelixDB Documentation to get you started with HelixDB",
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"keywords": "HelixDB, Documentation, Getting Started, CLI, SDK, Guides, Features, Blogs, RAG, Database, Database, Graph Database, Vector Database, AI, Agents, LLMs, Knowledge Graphs, Retrieval Augmented Generation, Knowledge Graphs, AI Agents, Document databases",
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"og:description": "HelixDB Documentation",
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"og:type": "website",
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"og:site_name": "HelixDB Documentation",
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"indexing": "all",
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"category": "Technology",
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"language": "en",
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"author": "HelixDB"

documentation/cli-v2/getting-started.mdx

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---
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title: "Getting Started"
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description: "Install, configure, and set up the Helix CLI v2 for your development workflow"
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title: "Getting started with HelixDB CLI v2"
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description: "Step-by-step guide to install, configure, and deploy your first HelixDB instance with CLI v2"
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icon: "rocket"
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---
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<Steps>
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<Step title="Quick Install">
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<Step title="How do I install the Helix CLI?">
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Use the official installer script to automatically download and set up the Helix CLI:
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```bash
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</Note>
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</Step>
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<Step title="Create project">
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<Step title="How do I create a new HelixDB project?">
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```bash
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helix init
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```
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</Step>
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<Step title="Create schema and queries">
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<Step title="How do I define schemas and queries?">
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Inside the schema.hx file, create your schema.
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```js
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N::User {
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</Step>
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<Step title="Build and deploy">
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<Step title="How do I deploy my HelixDB instance?">
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```bash
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helix push dev
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```
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</Step>
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<Step title="Test connection">
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<Step title="How do I test my HelixDB connection?">
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**Create a user**
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```bash
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curl -X POST http://localhost:6969/createUser -H 'Content-Type: application/json' -d '{"name": "John Doe", "email": "[email protected]"}'

documentation/getting-started/graph-database.mdx

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A graph database is a type of database that stores data using a graph structure, where information is represented through **nodes** (data points) and **edges** (relationships between nodes). Unlike traditional databases that use tables or documents, graph databases excel at managing highly connected data and complex relationships.
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## How Graph Databases Work
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## How do graph databases work?
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Graph databases are built on two fundamental concepts:
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Graph databases store data using two fundamental concepts:
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1. **Nodes** - These are the entities or objects in your data (like people, products, or locations)
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2. **Edges** (or relationships) - These are the connections between nodes that describe how they relate to each other
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- Edges show relationships like friendships, employment, and product interactions
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- Both nodes and edges can have properties (additional data attributes)
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## Common Use Cases
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## What are graph databases used for?
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### 1. Social Networks
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Perfect for modeling:
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- AI and machine learning
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- Research and discovery
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## When to Use a Graph Database
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## When should I use a graph database?
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Consider using a graph database when:
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Use a graph database when:
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- Your data has many interconnected relationships
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- You need to perform complex queries involving multiple relationships
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## Benefits Over Traditional Databases
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## What are the benefits of graph databases?
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1. **Performance**: Faster for relationship-heavy queries
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2. **Flexibility**: Easier to modify and extend the data model
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3. **Intuitive**: More natural way to model connected data
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4. **Scalability**: Better handling of complex relationship patterns
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## Next steps
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<CardGroup cols={2}>
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<Card title="What is HelixDB?" icon="database" href="/documentation/getting-started/helixdb">
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Learn about HelixDB's architecture and features
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</Card>
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<Card title="Getting started" icon="rocket" href="/documentation/cli-v2/getting-started">
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Install and deploy your first graph database
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</Card>
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<Card title="Social network guide" icon="users" href="/guides/social-network">
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Build a social network with graph databases
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</Card>
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<Card title="HelixQL basics" icon="book-open" href="/documentation/hql/hql">
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Learn to query graph data
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</Card>
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</CardGroup>

documentation/getting-started/helixdb.mdx

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Rust version 1.88.0 or higher is required. Make sure you have an updated version of Rust installed. Run `rustup update` to update your Rust version.
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</Warning>
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## Key Features
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## What are HelixDB's key features?
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HelixDB provides:
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- **High Performance**: Purpose-built storage engine optimized for both graph and vector operations
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- **Type Safety**: Explicit type definitions to ensure data integrity
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- **Developer-Friendly**: Simple setup and migration
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## Data Model
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## How does HelixDB store data?
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HelixDB follows the property graph model, which consists of:
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HelixDB uses a property graph model with three core components:
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- **Nodes**: Represent entities with unique identifiers and properties
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## Next steps
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<CardGroup cols={2}>
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<Card title="Getting started with CLI" icon="rocket" href="/documentation/cli-v2/getting-started">
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Install and deploy your first HelixDB instance
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</Card>
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<Card title="Learn HelixQL" icon="book-open" href="/documentation/hql/hql">
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Master the HelixQL query language
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</Card>
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<Card title="Schema definitions" icon="table" href="/documentation/hql/schema/schema-definition">
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Define your graph structure
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</Card>
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<Card title="Python SDK" icon="python" href="/documentation/sdks/helix-py">
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Use HelixDB with Python
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</Card>
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</CardGroup>

documentation/hql/create/addN.mdx

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title: "Nodes"
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description: "Learn how to create nodes in your graph."
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title: "Create nodes"
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description: "How to create nodes in your HelixDB graph with AddN including examples for empty nodes, parameterized nodes, and predefined properties"
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## Create Nodes using `AddN` &nbsp;
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## How do I create nodes in HelixDB?
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## Related operations
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- [Select nodes](/documentation/hql/select/selectN) - Query existing nodes
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- [Create edges](/documentation/hql/create/addE) - Connect nodes with relationships
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- [Update nodes](/documentation/hql/updating) - Modify node properties
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- [Schema definitions](/documentation/hql/schema/schema-definition) - Define node types

documentation/hql/hql.mdx

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title: "What is HelixQL?"
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description: "Learn about HelixQL, a strongly typed compiled query language for graph and vector operations in HelixDB"
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sidebarTitle: "What is HQL?"
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HelixQL is a strongly typed, compiled query language for HelixDB.
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It was inspired from a combination of Gremlin, Cypher and Rust.
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HelixQL is a strongly typed, compiled query language for HelixDB that combines the best features of Gremlin, Cypher, and Rust to provide type-safe graph and vector queries.
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## Why yet another query language?
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## Why use HelixQL instead of other query languages?
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HelixQL addresses key limitations found in existing graph query languages:
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- **Type safety**: Queries are validated at compile time, catching errors before runtime
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- **Readability**: Clean, concise syntax that remains readable even for complex queries
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- **Performance**: Compiled queries execute faster than dynamically parsed alternatives
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- **Developer experience**: IDE support with autocomplete and type checking
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## How do I write a HelixQL query?
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#### Components
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### Query components
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- `QueryName`: Identifier for the query

documentation/hql/schema/schema-definition.mdx

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title: "Schema Definition"
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description: "Text, title, and styling in standard markdown"
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title: "Schema definition"
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description: "How to define schemas for nodes, edges, and vectors in HelixDB with type-safe property definitions"
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### Node schemas
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documentation/hql/select/selectN.mdx

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description: "How to select and query nodes in your HelixDB graph by ID or type with code examples"
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## Related operations
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- [Create nodes](/documentation/hql/create/addN) - Add new nodes to your graph
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- [Traversals](/documentation/hql/traversals/steps_nodes) - Navigate between connected nodes
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- [Conditionals](/documentation/hql/conditionals/conditions) - Filter nodes by properties
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- [Property access](/documentation/hql/properties/property-access) - Work with node properties

documentation/hql/vectors/searching.mdx

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title: "Vector Search"
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title: "Vector search"
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description: "How to perform vector similarity search in HelixDB using cosine similarity with code examples"
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```rust
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