deeplake

Overview

Deeplake is an open-source AI data runtime that provides a serverless PostgreSQL-compatible multimodal datalake. It enables scalable retrieval and training for agent-based systems by storing and querying vectors, images, text, and other data types.

Best for

Best for
Developers building AI agents that need a unified, scalable datalake for retrieval and training

Use cases

• Store and query multimodal data for AI agent memory
• Build scalable retrieval pipelines for RAG applications
• Manage training datasets with versioning and streaming

Notes

Deeplake is an open-source AI data runtime that provides a serverless PostgreSQL-compatible multimodal datalake. It enables scalable retrieval and training for agent-based systems by storing and querying vectors, images, text, and other data types.

9,150 stars on GitHub. Last updated 2026-05-21. Licensed Apache-2.0.

Use cases

• Store and query multimodal data for AI agent memory
• Build scalable retrieval pipelines for RAG applications
• Manage training datasets with versioning and streaming

Pros

• Serverless architecture reduces operational overhead
• Multimodal support handles diverse data types in one system
• High GitHub popularity indicates active community and trust

Cons

• C++ codebase may limit rapid feature iteration
• Community-driven project may lack enterprise support
• Serverless model can introduce latency for real-time queries

Indexed from awesome-llmops and enriched against its public facts.