Vectra

🔌

Provider Agnostic

Switch between Pinecone, Qdrant, Weaviate, or pgvector with a single line change. No vendor lock-in.

🚀

Production Ready

Built for Ruby 3.2+ with comprehensive test coverage (95%+), retry logic, and circuit breakers.

📈

Observable

Grafana dashboard, Prometheus metrics, and native instrumentation for Datadog and New Relic. Track latency, throughput, and errors.

🏗️

Rails Ready

Seamless ActiveRecord integration with has_vector DSL and automatic migration support.

🔄

Resilient

Built-in retry logic with exponential backoff, jitter, and intelligent error recovery.

📚

Well Documented

Extensive YARD documentation, comprehensive examples, and detailed provider guides.

Comprehensive Feature Comparison

See how Vectra compares to other Ruby vector database clients

Feature	Vectra	Langchain.rb	pgvector-ruby	qdrant-ruby
Multi-Provider Support	✅ 5 providers	⚠️ 6+ (fragmented)	❌ PostgreSQL only	❌ Qdrant only
Unified API	✅ Single interface	❌ Provider-specific	❌ N/A	❌ N/A
Circuit Breaker	✅ Built-in	❌ Manual	❌ Manual	❌ Manual
Rate Limiting	✅ Token bucket	❌ Manual	❌ Manual	❌ Manual
Retry Logic	✅ Exponential backoff	❌ Manual	❌ Manual	⚠️ Basic
Instrumentation	✅ 4 backends	❌ None	❌ None	❌ None
Connection Pooling	✅ Built-in	❌ Manual	⚠️ Via pg gem	❌ Manual
Caching Layer	✅ TTL + LRU	❌ Manual	❌ Manual	❌ Manual
Health Checks	✅ 3 methods	❌ Manual	❌ Manual	❌ Manual
Rails Integration	✅ has_vector DSL	✅ Via langchainrb_rails	⚠️ Manual setup	⚠️ Manual setup
Query Builder	✅ Chainable API	❌ None	❌ None	❌ None
Batch Operations	✅ With progress	⚠️ Basic	❌ Manual	⚠️ Basic
Hybrid Search	✅ 4 providers	❌ Not documented	❌ Manual SQL	⚠️ Via API
Vector Normalization	✅ L2/L1 helpers	❌ Manual	❌ Manual	❌ Manual
Testing Support	✅ Mock provider	❌ Manual mocking	❌ Test DB	❌ Test server
Dimension Validation	✅ Automatic	❌ Manual	❌ Manual	❌ Manual
Error Handling	✅ 10 error types	⚠️ Basic	⚠️ Basic	⚠️ Basic
Audit Logging	✅ Built-in	❌ Manual	❌ Manual	❌ Manual
Credential Rotation	✅ Zero-downtime	❌ Manual	❌ Manual	❌ Manual
Test Coverage	✅ 95%+	⚠️ Not disclosed	⚠️ Not disclosed	⚠️ Not disclosed

Legend: ✅ Full Support | ⚠️ Partial/Limited | ❌ Not Available

Visual Comparison

See the difference at a glance

Feature Count Comparison

Vectra 22 features

Langchain.rb 10 features

qdrant-ruby 7 features

pgvector-ruby 6 features

Production Readiness

Multi-Provider

Production Patterns

Developer Experience

Testing Support

Observability

Documentation

Vectra scores 100% across all production readiness dimensions

Vectra Unique Advantages

What makes Vectra the best choice for Ruby developers

1. Only Unified Ruby Client

Single API za 5 različitih providera
Switch provider s 1 line of code
No Python envy needed

2. Enterprise Production Patterns

Circuit Breaker ✅
Rate Limiter ✅
Retry Logic ✅
Connection Pooling ✅
Caching ✅
Health Checks ✅
Audit Logging ✅

3. Developer Experience

Query Builder (chainable API)
Mock Provider (testing)
Dimension Validation
Enhanced Error Messages
Progress Callbacks

4. Rails-First Design

has_vector DSL
Automatic migrations
Seamless ActiveRecord integration

5. Observability Built-In

Datadog
New Relic
Sentry
Honeybadger

Which Solution Should You Choose?

Find the right tool for your needs

✅ Choose Vectra if you need:

Multi-provider support with single API
Production-grade resilience patterns
Rails integration with minimal setup
Enterprise observability
Easy testing without external dependencies

Choose Langchain.rb if you need:

LLM orchestration framework
RAG pipeline tools
Multi-modal AI workflows
Broader AI ecosystem integration

Choose pgvector-ruby if you:

Only use PostgreSQL
Need direct SQL control
Want minimal dependencies
Have existing Postgres infrastructure

Choose qdrant-ruby if you:

Only use Qdrant
Need Qdrant-specific features
Want direct API access
Self-host Qdrant

Quick Start

Get up and running in minutes

require 'vectra'

# Initialize any provider with the same API
client = Vectra::Client.new(
  provider: :pinecone,     # or :qdrant, :weaviate, :pgvector
  api_key: ENV['API_KEY'],
  host: 'your-host.example.com'
)

# Store vectors with metadata
client.upsert(
  vectors: [
    { 
      id: 'doc-1', 
      values: [0.1, 0.2, 0.3, ...],  # Your embedding
      metadata: { title: 'Getting Started with AI' }
    }
  ]
)

# Search by similarity
results = client.query(
  vector: [0.1, 0.2, 0.3, ...],
  top_k: 10,
  filter: { category: 'tutorials' }
)

results.each do |match|
  puts "#{match['id']}: #{match['score']}"
end

# Hybrid search (semantic + keyword)
results = client.hybrid_search(
  index: 'docs',
  vector: embedding,
  text: 'ruby programming',
  alpha: 0.7  # 70% semantic, 30% keyword
)

Vector Databases,
Unified for Ruby.

Provider Agnostic

Production Ready

Observable

Rails Ready

Resilient

Well Documented

Comprehensive Feature Comparison

Visual Comparison

Feature Count Comparison

Production Readiness

Vectra Unique Advantages

1. Only Unified Ruby Client

2. Enterprise Production Patterns

3. Developer Experience

4. Rails-First Design

5. Observability Built-In

Which Solution Should You Choose?

✅ Choose Vectra if you need:

Choose Langchain.rb if you need:

Choose pgvector-ruby if you:

Choose qdrant-ruby if you:

Supported Providers

Recipes & Patterns

🛒 E-Commerce Search

📝 Blog Hybrid Search

🏢 Multi-Tenant SaaS

🤖 RAG Chatbot

🔄 Provider Migration

💡 Recommendations

Quick Start

Vector Databases, Unified for Ruby.

Provider Agnostic

Production Ready

Observable

Rails Ready

Resilient

Well Documented

Comprehensive Feature Comparison

Visual Comparison

Feature Count Comparison

Production Readiness

Vectra Unique Advantages

1. Only Unified Ruby Client

2. Enterprise Production Patterns

3. Developer Experience

4. Rails-First Design

5. Observability Built-In

Which Solution Should You Choose?

✅ Choose Vectra if you need:

Choose Langchain.rb if you need:

Choose pgvector-ruby if you:

Choose qdrant-ruby if you:

Supported Providers

Recipes & Patterns

🛒 E-Commerce Search

📝 Blog Hybrid Search

🏢 Multi-Tenant SaaS

🤖 RAG Chatbot

🔄 Provider Migration

💡 Recommendations

Quick Start

Vector Databases,
Unified for Ruby.