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Contexta vs Graph databases

A graph database is the right primitive for richly connected data — but a general-purpose graph DB does not know what an agent needs. Contexta is graph-native, but it ships the agent half of the stack: ingest from unstructured sources, Reflex triggers, Context Packet output, agent-tuned retrieval, and a hosted runtime. If you want raw Cypher tooling, use Neo4j. If you want a context layer, use Contexta.

  • Neo4j
  • ArangoDB
  • TigerGraph
  • Memgraph
  • JanusGraph
TL;DR

Neo4j stores graphs. Contexta turns graphs into context.

  • Graph-native storage

    Contexta
    Graph DB
  • Turnkey ingest from unstructured sources

    Contexta
    Graph DB
    DIY
  • Provenance / receipts on every fact

    Contexta
    Graph DB
    DIY
  • Reactive triggers (Reflexes) on graph patterns

    Contexta
    Graph DB
    Limited
  • Bi-temporal recall built in

    Contexta
    Graph DB
  • Context Packet output for LLMs

    Contexta
    Graph DB
  • Agent-tuned retrieval API

    Contexta
    Graph DB
  • Deep Cypher / Gremlin tooling

    Contexta
    CX motifs
    Graph DB
  • Hosted vs. DIY

    Contexta
    Hosted + self-host
    Graph DB
    Hosted + self-host

When to choose Contexta

  • You want an agent context layer that happens to be graph-native — not a graph DB you have to wrap.
  • You need turnkey ingest from Slack, email, tickets, docs, and event streams.
  • You want to fire on graph patterns without writing your own subscription engine.
  • You need Context Packets, citations, and policy enforcement bundled with retrieval.

When NOT to choose Contexta yet

  • You need a general-purpose graph DB with deep Cypher tooling — use Neo4j.
  • Your workload is graph analytics (PageRank, community detection) at OLAP scale — use a dedicated engine.
FAQ

Common questions

Related

Other category breakdowns

vs Vector RAG

Vector RAG retrieves snippets. Contexta returns Context Packets with receipts.

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vs Memory libraries

Mem0, Letta and Zep give you storage. Contexta gives you a context layer.

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vs Workflow automation

Zapier and n8n react to flat events. Contexta reacts to graph state.

Read →

vs Agent frameworks

LangGraph and CrewAI build the agent loop. Contexta is the context layer underneath.

Read →

See why teams pick Contexta over Graph databases.

Drop your evaluation criteria — we will price honestly against your signal volume and ship you a Context Packet to inspect.