# Activeloop Deep Lake

> Multi-modal tensor DB for vectors/images/texts/videos with hybrid embedding + metadata/tensor search. Supports multimodal RAG datasets with versioning. Data lake scale vs pure vector stores like Qdrant.

- **URL:** https://www.activeloop.ai
- **Category:** Multimodal Vector Databases
- **Tags:** Multimodal, 2026 Trends, Tensor, Vision Text, Clip Compatible, Hybrid Search
- **Updated:** 2026-04-29 11:31
- **Canonical page:** https://vectordb.ever.works/items/activeloop-deep-lake

## Details

## Overview

Deep Lake is Activeloop's open-source database designed for complex, unstructured data. It combines the benefits of a traditional data lake with modern vector database capabilities and tensor storage.

## Hybrid Capabilities

- Embeddings search + metadata/tensor filtering.

## Features

- **Multi-Modal Tensor Storage**: Images, audio, video, annotations, tables stored as tensors
- **Columnar Storage**: Chunked compressed arrays for rapid streaming
- **Time Travel**: Git-like versioning - see changes, roll back, branch off
- **ACID Transactions**: Full transactional support
- **Terabyte Visualization**: Visualize massive datasets
- **Multi-Cloud Support**: S3, Azure, GCP, local, or Activeloop cloud
- **ML Framework Integration**: Built-in dataloaders for PyTorch and TensorFlow
- **Hybrid Search**: Embeddings and metadata search

## Managed Tensor Database (2026)

Serverless managed service that eliminates self-hosting complexity and substantially lowers costs. Specify `runtime = {"tensor_db": True}` when creating Vector Store.

## Use Cases

- Multimodal RAG data pipelines.
- Deep learning with multimodal data
- Computer vision applications
- Audio/video processing
- Scientific data management
- Large-scale ML training pipelines
- Versioned dataset management

## Comparisons vs Pure Vector DBs (e.g., Qdrant)

Data lake for multimodal vs vector index.

## Integration

Works with LangChain, LlamaIndex, and major ML frameworks. Compatible with any S3-compatible storage including MinIO.

## Pricing

Open-source for self-hosting. Managed Tensor Database offers serverless pricing with usage-based costs.

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