Vector database for ML training at scale
Shyft Score
Directory quality rating
Our take
Activeloop provides a database for AI, offering tools for data storage and management. Its focus on AI makes it a valuable tool for engineering teams.
Best for: Engineering teams seeking an AI-driven database solution
Request a demo to evaluate Activeloop for your team.
See how Activeloop fits your stackBenefits
Cut data pipeline setup time from weeks to hours
Scale storage seamlessly without infrastructure headaches
Track data changes automatically to prevent model failures
Access all your ML data through one simple API
About
Activeloop is a vector database optimized for AI/ML workloads. It provides Python-native data versioning, real-time updates, and seamless integration with PyTorch and TensorFlow. Use it to version and query large datasets (10GB-10TB+) for training models at scale.
Real-time data management
Scalable storage solutions
Seamless integration with machine learning frameworks
Data versioning and lineage tracking
User-friendly API for data access
Category
Database
Department
Engineering
Pricing
Subscription (from $29/mo)
GitHub stars
9.1k
Website
activeloop.ai
Use cases
Version control for ML training datasets
Storing and querying embeddings at scale
Real-time dataset updates during model training
PyTorch/TensorFlow pipeline integration
Best for
Pricing
Activeloop starts at $29/mo
Starting at $29/mo
Ecosystem
MCP servers, AI skills, and integrations that work with Activeloop
FAQs
Common questions about Activeloop and its capabilities
Activeloop is an AI-optimized database for engineering teams, best suited for data scientists, AI developers, and machine learning engineers. It offers features like real-time data management and seamless integration with machine learning frameworks.
Our team can help you integrate Activeloop with your existing tools and build custom automation workflows.
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