activeloopai/deeplake
🔧 Toolactiveloopai
AI Data Runtime for Agents: serverless Postgres with multimodal datalake for scalable retrieval & training.
Deeplake is a high-performance AI data runtime designed for agentic workflows. Built in C++ with Python bindings, it combines a serverless Postgres database with a multimodal datalake to store and query text, images, videos, and embeddings. Key features include scalable vector search, data versioning, streaming data loading, and integration with major deep learning frameworks. It supports agent memory, RAG pipelines, and MLOps workflows, making it a unified solution for data management in AI applications. With over 9k GitHub stars, Deeplake is actively maintained and used by developers building production-grade AI agents.
💡Highlights
- ├─Serverless Postgres with multimodal lake
- ├─Scalable retrieval & training for agents
- └─9.2k stars, active open-source project
🎯For
- ├─AI Developers
- ├─ML Engineers
- └─Agent Builders