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What is an AI Database?

AI databases are a fast-emerging database approach dedicated to creating better machine-learning and deep-learning models and then train them faster and more efficiently. AI databases integrate artificial intelligence technologies to provide value-added services. Targeted at optimizing compute and database resources, AI databases can simultaneously ingest, explore, analyze, and visualize fast-moving, complex data in milliseconds. AI databases provide full-text search and text-analytics capabilities.

When to use an AI database

  • For applications that require faster ingestion and more processing speed.
  • To reach business goals dependent on your organization’s machine-learning and deep-learning efforts.
  • To build a model pipeline platform that performs data-science-driven model hosting.
  • To address the volume, velocity, and complex data governance and management challenges associated with training machine-learning and deep-learning models to save time and optimize resources.

Use cases for AI databases

  • Object detection and text analytics.
  • Speech recognition.
  • Social-network filtering.
  • Visual inspection.
  • Natural language processing.


RedisAI is a Redis module for executing deep learning/machine learning models and managing their data. It provides tensors as a data type and deep-learning model execution on CPUs and GPUs. RedisAI turns Redis Enterprise into a full-fledged deep- learning runtime.