deeplake

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

9.0k

Stars

+113

Gained

1.3%

Growth

C++

Language

View on GitHub → ↑0.1% this week

💡 Why It Matters

DeepLake addresses the challenge of managing diverse AI data types, such as vectors, images, and videos, in a cohesive manner. This is particularly beneficial for ML and AI teams that require a robust database to store, query, and visualise their datasets efficiently. With a steady growth of stars, it indicates a stable community interest, suggesting it is a production-ready solution suitable for real-world applications. However, it may not be the right choice for teams looking for a lightweight or less complex data management system, as its comprehensive features may be overkill for simpler projects.

🎯 When to Use

DeepLake is a strong choice when teams need a scalable and versatile solution for managing large datasets in AI projects. However, if a project requires a simpler database or has minimal data management needs, teams should consider alternatives.

👥 Team Fit & Use Cases

This open source tool for engineering teams is ideal for data scientists, machine learning engineers, and AI researchers who need to handle complex datasets. It is commonly integrated into products and systems that involve real-time data processing and AI model training.

🎭 Best For

Machine Learning and AI Engineer

🏷️ Topics & Ecosystem

ai computer-vision cv data-science datalake datasets deep-learning image-processing langchain large-language-models llm machine-learning ml mlops multi-modal python pytorch tensorflow vector-database vector-search

📊 Activity

Latest commit: 2026-02-14. Over the past 97 days, this repository gained 113 stars (+1.3% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.