All Tools
A
DataFreemiumOpen Source
ACTIVELOOP
Serverless data lake with vector search for AI applications
Apache-2.0
ABOUT
AI applications need to store, version, query, and stream multimodal training and inference data — text, images, video, embeddings — but traditional databases and object stores lack the integration needed for modern AI pipelines. Activeloop's DeepLake provides a unified data runtime that combines a vector store for RAG, a data lake for versioned datasets, and streaming to GPUs, all with a simple Python API that works like a dictionary.
INSTALL
pip install deeplakeINTEGRATION GUIDE
1. Store and query large-scale vector embeddings for RAG applications
2. Manage versioned training datasets for computer vision and NLP models
3. Build agent memory systems with multimodal data (text, images, video)
4. Stream training data directly to GPU memory without local disk staging
5. Create hybrid search pipelines combining vector similarity with metadata filtering
TAGS
data-lakevector-databaseembeddingscomputer-visionnlppythondata-pipeline