How dig compares
dig is the local, reversible knowledge-base layer your agent retrieves from. Here is where it sits next to memory services, vector databases, RAG frameworks, and note apps — and when to pick which.
dig vs Letta (MemGPT) — a memory layer, not an agent framework
Letta (formerly MemGPT) is an agent framework with tiered self-managed memory. dig is the data + memory layer underneath any agent — local, reversible, framework-agnostic.
dig vs LlamaIndex — the local data layer under a RAG framework
LlamaIndex is a framework for building RAG pipelines — loaders, indexes, query engines. dig is the local, reversible data and retrieval layer such a framework can sit on. They compose; they don't compete.
dig vs mem0 — local-first memory without a vector database
mem0 is a pluggable memory SDK that needs a vector store. dig is a local-first CLI + MCP server with built-in hybrid retrieval and reversible history. When to pick which.
dig vs Obsidian — dig organizes the vault Obsidian edits
Obsidian is a local Markdown editor for your notes. dig is the agent that keeps the vault organized, deduped, and searchable — and it coexists with Obsidian instead of replacing it.
dig vs hosted RAG-as-a-service — local-first ownership over a managed pipeline
RAG-as-a-service runs a managed cloud pipeline that ingests your documents and answers over them. dig is a local-first retriever you own — hybrid search, reversible history, no data leaving your machine.
dig vs a vector database — a complete retriever, not storage to operate
A vector database (Pinecone, Weaviate, Qdrant, Chroma) is storage you run and embed into. dig is a complete local retriever — hybrid FTS plus vector, management, and reversibility, with no service to operate.
dig vs Zep — local, reversible agent memory without a hosted service
Zep is a hosted agent-memory service built on a temporal knowledge graph. dig is local-first memory you own — hybrid retrieval, reversible history, no service to run. When to pick which.