Welcome to the Vector Database Cloud Playbook! This repository is a comprehensive collection of test scenarios, implementation guides, and best practices for using vector databases like pgvector, Milvus, Qdrant, and ChromaDB. The Playbook serves as a resource for developers and contributors to learn, implement, and optimize vector database solutions.
- About Vector Database Cloud
- Introduction
- Prerequisites
- Test Scenarios
- Implementation Guides
- Scripts
- Examples
- Documentation
- Usage
- Troubleshooting
- Contributing
- License
- Disclaimer
Vector Database Cloud is a platform that provides one-click deployment of popular vector databases including Qdrant, Milvus, ChromaDB, and Pgvector on cloud. Our platform ensures a secure API, a comprehensive customer dashboard, efficient vector search, and real-time monitoring.
Vector Database Cloud is designed to seamlessly integrate with your existing data workflows. Whether you're working with structured data, unstructured data, or high-dimensional vectors, you can leverage popular ETL (Extract, Transform, Load) tools to streamline the process of moving data into and out of Vector Database Cloud.
The Playbook provides practical "recipes" for various use cases and technical challenges involving vector databases. Whether you're looking to test a specific scenario, deploy a new setup, or optimize an existing system, you'll find valuable resources here.
- Python 3.7+
- Access to Vector Database Cloud services
- Basic understanding of vector databases and their applications
Explore our detailed test scenarios, categorized by vector database technology:
- pgvector: Test cases and scenarios specific to pgvector.
- Milvus: Scenarios designed to test Milvus's capabilities and performance.
- Qdrant: Test setups for Qdrant applications.
- ChromaDB: Specific scenarios for testing ChromaDB functionalities.
Step-by-step instructions for various implementations:
- Deployment: How to deploy vector databases in various environments.
- Optimization: Best practices and techniques for optimizing performance.
- Integration: Integrating vector databases with other technologies.
Find useful scripts for automating tasks and managing setups:
- Setup Scripts: Scripts for environment setup and configuration.
- Test Automation: Automating test execution and result collection.
Certainly. I'll continue from the Examples section:
## Examples
Real-world use cases and examples:
- **[Example Projects](examples/)**: Demonstrations of how vector databases are applied in different scenarios.
## Documentation
Additional resources and detailed documentation:
- **[Architecture Diagrams](docs/architecture/)**: Visual representations of system architectures.
- **[Data Flow](docs/data-flow/)**: Explanation of data flows and processing.
## Usage
To use this playbook:
1. Clone the repository:git clone https://github.com/VectorDBCloud/Playbook.git cd Playbook
2. Navigate to the specific section you're interested in (e.g., Test Scenarios, Implementation Guides).
3. Follow the README files in each directory for specific instructions.
## Troubleshooting
If you encounter issues:
1. Check the specific README file in the relevant directory for known issues and solutions.
2. Ensure all prerequisites are met and environment variables are correctly set.
3. Verify your Vector Database Cloud account has the necessary permissions.
4. For persistent problems, please create an issue in this repository.
## Contributing
We welcome contributions to improve and expand our Open-Source Embedding Cookbook! Here's how you can contribute:
1. **Fork the repository**: Create your own fork of the code.
2. **Create a new branch**: Make your changes in a new git branch.
3. **Make your changes**: Enhance existing cookbooks or add new ones.
4. **Follow the style guidelines**: Ensure your code follows our coding standards.
5. **Write clear commit messages**: Your commit messages should clearly describe the changes you've made.
6. **Submit a pull request**: Open a new pull request with your changes.
7. **Respond to feedback**: Be open to feedback and make necessary adjustments to your pull request.
For more detailed information on contributing, please refer to our [Contribution Guidelines](CONTRIBUTING.md).
## License
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright (c) 2024 Vector Database Cloud
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially
Under the following terms:
- Attribution — You must give appropriate credit to Vector Database Cloud, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests Vector Database Cloud endorses you or your use.
Additionally, we require that any use of this guide includes visible attribution to Vector Database Cloud. This attribution should be in the form of "Playbooks curated by Vector Database Cloud" or "Based on Vector Database Cloud Playbooks", along with a link to https://vectordbcloud.com, in any public-facing applications, documentation, or redistributions of this guide.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
For the full license text, visit: https://creativecommons.org/licenses/by/4.0/legalcode
## Disclaimer
The information and resources provided in this community repository are for general informational purposes only. While we strive to keep the information up-to-date and correct, we make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability or availability with respect to the information, products, services, or related graphics contained in this repository for any purpose. Any reliance you place on such information is therefore strictly at your own risk.
Vector Database Cloud configurations may vary, and it's essential to consult the official documentation before implementing any solutions or suggestions found in this community repository. Always follow best practices for security and performance when working with databases and cloud services.
The content in this repository may change without notice. Users are responsible for ensuring they are using the most current version of any information or code provided.
This disclaimer applies to Vector Database Cloud, its contributors, and any third parties involved in creating, producing, or delivering the content in this repository.
The use of any information or code in this repository may carry inherent risks, including but not limited to data loss, system failures, or security vulnerabilities. Users should thoroughly test and validate any implementations in a safe environment before deploying to production systems.
For complex implementations or critical systems, we strongly recommend seeking advice from qualified professionals or consulting services.
By using this repository, you acknowledge and agree to this disclaimer. If you do not agree with any part of this disclaimer, please do not use the information or resources provided in this repository.