Comparison / Open Source AI Memory Database

Agent Memory vs Vector Database

A vector database is useful for semantic search, but agent memory also needs durable event ingest, lifecycle management, graph context, shared knowledge, and retrieval controls.

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The problem this solves

Vector-only memory tends to flatten facts, procedures, events, tasks, and relationships into one retrieval path.

How Memorose handles it

Memorose keeps vector search as one part of a broader memory runtime that also includes full-text retrieval, graph expansion, time filters, multimodal ingest, and forgetting workflows.

runtime example

agent_memory = {
  events,
  durable_memories,
  embeddings,
  full_text_index,
  graph_links,
  lifecycle_controls
}