fleet-memory/docker/docker-compose/timescale

Hindsight with Timescale Extensions

This Docker Compose setup provides a complete Hindsight deployment with Timescale extensions:

• pgvectorscale - DiskANN algorithm for disk-based scalable vector search
• pg_textsearch - High-performance BM25 text search

Both extensions are from Timescale and provide production-grade performance.

Prerequisites

• Docker and Docker Compose installed
• OpenAI API key (or another LLM provider)

Quick Start

# Set environment variables
export HINDSIGHT_DB_PASSWORD="your-secure-password"
export OPENAI_API_KEY="your-openai-api-key"

# Build and start
docker compose -f docker/docker-compose/timescale/docker-compose.yaml up -d --build

# Check logs

docker compose -f docker/docker-compose/timescale/docker-compose.yaml logs -f

Access:

• API: http://localhost:8888
• Control Plane: http://localhost:9999

Stop and Clean Up

# Stop services
docker compose -f docker/docker-compose/timescale/docker-compose.yaml down

# Remove volumes (deletes all data)
docker compose -f docker/docker-compose/timescale/docker-compose.yaml down -v

Configuration

Environment Variables

Variable	Description	Default
HINDSIGHT_DB_PASSWORD	PostgreSQL password	hindsight_password
HINDSIGHT_DB_USER	PostgreSQL username	hindsight_user
HINDSIGHT_DB_NAME	Database name	hindsight_db
HINDSIGHT_VERSION	Hindsight Docker image version	latest
OPENAI_API_KEY	OpenAI API key	(required)
HINDSIGHT_API_LLM_PROVIDER	LLM provider	openai

Why Timescale Extensions?

pgvectorscale (DiskANN):

• 28x lower p95 latency vs dedicated vector databases
• 16x higher query throughput at 99% recall
• 60-75% cost reduction (disk is cheaper than RAM)
• Best for large datasets (10M+ vectors)

pg_textsearch (BM25):

• High-performance keyword retrieval
• Native BM25 ranking algorithm
• Optimized for full-text search

Troubleshooting

Extensions not installed

Check if extensions are available:

docker exec -it hindsight-db-timescale psql -U hindsight_user -d hindsight_db -c "\dx"

You should see:

• vector (pgvector)
• vectorscale (pgvectorscale/DiskANN)
• pg_textsearch (BM25 search)

Build fails

If the Docker build fails during pgvectorscale compilation:

1. Ensure you have sufficient memory (recommended: 4GB+)
2. Check Docker build logs for Rust compilation errors
3. Try building with more resources: docker compose build --no-cache --memory 4g

Port conflicts

If port 5438 is already in use, modify the ports section in docker-compose.yaml.

Learn More

• pgvectorscale GitHub
• pg_textsearch GitHub
• HNSW vs DiskANN
• Hindsight Documentation