- Home
- Data & Databases
- Deeplake
Deeplake
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake,
Rating
Votes
0
score
Downloads
0
total
Price
Free
No login needed
Works With
About
Deep Lake: Database for AI
Docs • Get Started • API Reference • LangChain & VectorDBs Course • Blog • Whitepaper • Slack • Twitter
What is Deep Lake?
Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for:
- 1.Storing and searching data plus vectors while building LLM applications
- 2.Managing datasets while training deep learning models
Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, dicom, pdfs, annotations, and more), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.
Deep Lake includes the following features:
Multi-Cloud Support (S3, GCP, Azure) Use one API to upload, download, and stream datasets to/from S3, Azure, GCP, Activeloop cloud, local storage, or in-memory storage. Compatible with any S3-compatible storage such as MinIO.
Native Compression with Lazy NumPy-like Indexing Store images, audio, and videos in their native compression. Slice, index, iterate, and interact with your data like a collection of NumPy arrays in your system's memory. Deep Lake lazily loads data only when needed, e.g., when training a model or running queries.
Dataloaders for Popular Deep Learning Frameworks Deep Lake comes with built-in dataloaders for Pytorch and TensorFlow. Train your model with a few lines of code - we even take care of dataset shuffling. :)
Integrations with Powerful Tools Deep Lake has integrations with Langchain and LLamaIndex as a vector store for LLM apps, Weights & Biases for data lineage during model training, MMDetection for training object detection models, and MMSegmentation for training semantic segmentation models.
100+ most-popular image, video, and audio datasets available in seconds Deep Lake community has uploaded 100+ image, video and audio datasets like MNIST, COCO, ImageNet, CIFAR, GTZAN and others.
Instant Visualization Support in the Deep Lake App Deep Lake datasets are instantly visualized with bounding boxes, masks, annotations, etc. in Deep Lake Visualizer (see below).
[](https://www.youtube.com/watch?v=SxsofpSIw3k)
🚀 How to install Deep Lake
Deep Lake can be installed using pip:
pip install deeplakeTo access all of Deep Lake's features, please register in the Deep Lake App.
🧠 Deep Lake Code Examples by Application
Don't lose this
Three weeks from now, you'll want Deeplake again. Will you remember where to find it?
Save it to your library and the next time you need Deeplake, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, . Best for anyone looking to make their AI assistant more capable in data & databases. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
Your data stays between you and your AI — nothing is shared with us or anyone else.
What's New
Imported from GitHub
Ratings & Reviews
0.0
out of 5
0 ratings
No reviews yet. Be the first to share your experience.