CyborgDB Service provides a self-hosted microservice deployment with REST API and client SDKs. This model offers the perfect balance between control and convenience - you maintain ownership of your infrastructure while enjoying the benefits of a service-oriented architecture.

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Why Choose CyborgDB Service?

Faster Development
REST API and multi-language SDKs accelerate development across different teams and technology stacks. Built for Scale
Designed for high-throughput production workloads with horizontal scaling capabilities and connection pooling. DevOps Friendly
Docker-based deployment with comprehensive monitoring, logging, and operational tooling built-in. Multi-Language Support
Native SDKs for Python, JavaScript/TypeScript, Go, and C++ - use your preferred language stack.

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Deployment Options

Docker Deployment

Containerized service deployment
  • Self-contained Docker image
  • Easy Kubernetes integration
  • Production-ready configuration
  • Automatic dependency management
  • Best for: Production deployments, containerized environments

Python Service

Direct Python installation
  • Pip-installable service package
  • Custom Python environment control
  • Lightweight alternative to Docker
  • Direct dependency management
  • Best for: Python-centric environments, development

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Client SDKs

Access CyborgDB Service from any language using our comprehensive SDK collection:

Python SDK

Full-featured Python clientComplete client with async support and type hints

JavaScript/TypeScript SDK

Modern web and Node.js clientPromise-based API with TypeScript definitions

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Quick Start Paths

Docker Quickstart

Deploy in 5 minutesGet CyborgDB Service running with Docker and start building immediately.

Python Service Quickstart

Python-native deploymentInstall and run CyborgDB as a Python service with pip.

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API Key Limitations

Free API Key Users: If you’re using a free API key, CyborgDB Service will automatically use cyborgdb-lite under the hood, which includes:
  • Up to 1M vectors maximum
  • 4 CPU threads limit
  • PostgreSQL and Memory backing stores only
  • No GPU acceleration
Upgrade to a paid plan to unlock cyborgdb-core with unlimited vectors, all backing stores, GPU acceleration, and full performance capabilities.

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Architecture Overview

CyborgDB Service runs as a containerized microservice in your infrastructure: Key Benefits:
  • Language-agnostic API access
  • Horizontal scaling capabilities
  • Operational monitoring and logging
  • Production-ready deployment patterns

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When to Use Service vs Embedded

  • Multi-language teams - Need to support different programming languages
  • Microservice architecture - Want to separate vector operations from application logic
  • Operational simplicity - Prefer service-based deployment patterns
  • Horizontal scaling - Need to scale vector operations independently
  • Team collaboration - Multiple teams need access to the same vector data
  • REST API preference - Want standard HTTP endpoints for integration

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Production Considerations

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Scaling and Performance

  • Horizontal Scaling: Deploy multiple service instances behind a load balancer
  • Connection Pooling: Configure database connections for high concurrency
  • Caching: Use Redis backing store for low-latency workloads
  • Monitoring: Enable telemetry and monitoring for production visibility

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Security

  • API Key Management: Rotate keys regularly and use environment variables
  • Network Security: Deploy within private networks or use TLS/SSL
  • Database Security: Secure backing store connections and credentials
  • Access Control: Implement proper authentication and authorization

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Next Steps

Deploy with Docker

Get CyborgDB Service running with Docker

Deploy with Python

Install and run CyborgDB as a Python service

Explore REST API

Learn how to interact with CyborgDB Service via REST API
Ready to deploy CyborgDB as a scalable service? Start with our Docker Quickstart guide!