AWS OpenSearch k-NN

Overview

AWS OpenSearch Service provides k-nearest neighbor (k-NN) search capabilities for finding nearest neighbors in vector space by Euclidean distance or cosine similarity. Powered by NMSLIB, Faiss, and Lucene ANN libraries.

Key Features

Vector Field Type

• knn_vector field: Store dense vectors
• Dimensions: Up to 16,000 dimensions
• Configurable: Flexible vector configuration

Search Algorithms

• HNSW: Hierarchical Navigable Small World
• Faiss: Facebook AI Similarity Search
• Lucene: Apache Lucene k-NN
• Approximate k-NN: Fast searches on large datasets

Distance Metrics

• Euclidean distance
• Cosine similarity
• Dot product similarity
• Support for 16,000 dimensions

Implementation

Index Configuration

Create index with index.knn setting:

{
  "settings": {
    "index.knn": true
  },
  "mappings": {
    "properties": {
      "vector_field": {
        "type": "knn_vector",
        "dimension": 768
      }
    }
  }
}

Query Syntax

{
  "query": {
    "knn": {
      "vector_field": {
        "vector": [0.1, 0.2, ...],
        "k": 10
      }
    }
  }
}

Serverless Option

Vector Engine for OpenSearch Serverless

• Powered by k-NN feature
• No server management
• Automatic scaling
• Pay per use
• Simplified operations

Use Cases

• Recommendations: "Other songs you might like" features
• Image Recognition: Visual similarity search
• Fraud Detection: Pattern matching
• Semantic Search: Content discovery
• Anomaly Detection: Outlier identification

Integration with AWS Services

• S3: Vector engine with S3 backend
• Lambda: Serverless processing
• SageMaker: ML model integration
• Kinesis: Real-time data ingestion
• CloudWatch: Monitoring and alerting

Advanced Features

Vector Search Techniques

• Approximate k-NN search
• Exact brute-force search
• Filtered vector search
• Hybrid search (vectors + text)

Performance Optimization

• Index tuning
• Query optimization
• Cache configuration
• Shard allocation

Deployment Options

Managed Service

• Fully managed clusters
• Automatic updates
• Multi-AZ deployment
• VPC isolation

Serverless

• No infrastructure management
• Automatic scaling
• Cost-effective for variable workloads

Security

• VPC isolation
• Encryption at rest and in transit
• IAM integration
• Fine-grained access control
• Audit logging

Monitoring

• CloudWatch metrics
• Performance insights
• Query analytics
• Resource utilization
• Custom dashboards

High Availability

• Multi-AZ deployment
• Automatic failover
• Snapshot backups
• Point-in-time recovery

GitHub Resources

• k-NN plugin: opensearch-project/k-NN
• Examples and documentation
• Community contributions

Pricing

Commercial managed service with usage-based pricing:

Managed Clusters

• Instance hours: Per instance type and size
• Storage: Per GB-month (EBS or UltraWarm)
• Data transfer: Standard AWS data transfer rates

Serverless

• OCU (OpenSearch Compute Units): Per OCU-hour
• Storage: Per GB-month
• No minimum: Pay only for usage

Free Tier

• 750 hours of t2.small or t3.small instance
• 10GB monthly storage (first 12 months for new AWS customers)

Detailed pricing: aws.amazon.com/opensearch-service/pricing/