AI/ML Feature Store

Accelerate machine learning with vector embeddings and graph features

The ML Engineering Challenge

Machine learning teams need a centralized feature store that can:

  • Store and serve features with low latency for inference
  • Support vector embeddings from deep learning models
  • Compute graph-based features (centrality, PageRank, community detection)
  • Maintain feature versioning and lineage
  • Enable real-time feature computation
  • Support both batch and streaming pipelines

Existing feature stores often lack native support for vectors and graphs, forcing teams to cobble together multiple systems.

Why ArcadeDB for ML?

  • Native Vector Support: Store embeddings alongside features
  • Graph Features: Compute network-based features in real-time
  • Fast Retrieval: Serve features in <10ms for inference
  • Feature Engineering: Combine multiple data models in single queries
  • Scalability: Handle billions of feature vectors efficiently

ML Feature Engineering

ArcadeDB serves as a unified feature store for ML pipelines, combining user embeddings, basic statistical features (age, tenure, ratings), and graph-computed features (PageRank, community detection, centrality metrics) in real-time. This multi-model approach eliminates the need for separate vector and graph databases, reducing latency and infrastructure complexity while enriching model inputs with relationship-based features.

Production ML Deployment

"We use ArcadeDB as our feature store for all production ML models. The ability to combine vector embeddings with graph-computed features in real-time dramatically improved our model performance. Feature serving latency dropped from 45ms to under 10ms, enabling true real-time personalization. The multi-model approach eliminated three separate databases from our stack."

— ML Platform Lead, Technology Unicorn
(Company name confidential)

ML Performance Gains:

  • 78% reduction in feature serving latency (45ms → 10ms)
  • 12% improvement in model accuracy with graph features
  • 3 databases consolidated into 1
  • Real-time feature computation at 100K+ req/sec

Ready to Accelerate Your ML Pipelines?

Start exploring ArcadeDB today and discover how our unified feature store can transform your machine learning workflows.

Get Started Read Documentation