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Comparison / Onyx (Danswer)

A governed AI coworker, not a DIY toolkit.

Onyx (formerly Danswer) is a genuinely good open-source AI search project — if you want to self-assemble and operate it. ZenSearch is a Go-core coworker that answers with citations and takes governed action: risk-tiered approvals, pre-flight cost ceilings, and a managed SaaS option with commercial support, on your own infrastructure.

The Short Version

Choose ZenSearch if you need:

  • A Go core with lower baseline memory and better concurrency under load
  • Governed agent actions — risk tiers T0–T5, cross-surface approvals, cost ceilings
  • Built-in input + output guardrails (prompt injection, PII, hallucination)
  • Natural-language queries against PostgreSQL, MySQL, ClickHouse, and SQL Server
  • A managed SaaS option with commercial support, not a self-operated toolkit

Choose Onyx (Danswer) if you need:

  • A fully open-source codebase with community contributions
  • Self-hosted deployment with complete source access and no vendor
  • Python ecosystem compatibility for custom extensions
  • No commercial license required to run the core

Feature by Feature

ZenSearch vs Onyx (Danswer), in detail.

Agents & AI Capabilities

CapabilityZenSearchOnyx (Danswer)
Hybrid search (dense + sparse)
Cross-encoder reranking
Vector search
Retrieval augmented generation
Cited answers with sources
AI agents with tool calling
Faceted search & filtering
Custom agent builder
Limited
Approval-gated write actions
Every consequential write pauses on a per-team policy and routes to the right human
Risk tiers T0–T5Not available
Cross-surface approvals
Slack, Teams, and webNot available
Scheduled automations
Cron + event triggersNot available
Multi-agent delegation
Agents hand off subtasks to specialist agents in the same team via discover_agents + delegate_to_agent
Self-improving procedural memory
Distills successful multi-tool sessions into reusable procedures the agent automatically references on similar future queries
Observational memory (long-conversation compression)
80%+ token compression on 50+ message conversations via a cacheable LLM-extracted system prompt prefix
Agent memory & checkpointing
Three-layer memory stack: persistent facts, observational compression, procedural workflows
NL-to-SQL database queries
Query PostgreSQL, MySQL, ClickHouse, SQL Server with natural language
Answer confidence scoring
Guardrails (hallucination, PII, injection)
Slack / Teams / Chrome surfaces
Slack, Teams, ChromeSlack only

Deployment & Architecture

CapabilityZenSearchOnyx (Danswer)
Cloud (SaaS)
On-premise deployment
Air-gapped deployment
Limited
Docker & Kubernetes
Bring your own LLM
Model Gateway with usage tracking
Centralized proxy for all AI model calls with per-tenant cost tracking and per-team rate limits
Multi-tenant SaaS
Onyx is single-tenant only

Data Connectors

CapabilityZenSearchOnyx (Danswer)
Confluence
Slack
GitHub
Google Drive
SharePoint
Jira
Notion
Salesforce
SAP
HubSpot
PostgreSQL / MySQL / SQL Server
NL-to-SQL with schema discovery and query validation
ClickHouse
S3 / Azure Blob
Web Crawler

Security & Compliance

CapabilityZenSearchOnyx (Danswer)
SOC 2 Type II
In progress
Document-level RBAC
Permission-aware search
End-to-end encryption
Partial
Audit logging
Limited
Input/output guardrails
Prompt injection detection
PII detection & filtering

Performance & Infrastructure

CapabilityZenSearchOnyx (Danswer)
Primary language
Go services for search, API, and vectorization deliver lower latency and memory usage
GoPython
Pipeline architecture
NATS JetStream enables parallel processing and exactly-once delivery
Event-driven (NATS)Celery tasks
Vector database
Both are production-grade; Qdrant has a simpler operational footprint
QdrantVespa
Embedding caching
Redis-backed embedding cache reduces API costs on repeated content
Incremental sync

Where ZenSearch Stands Apart

Governed and supported, vs assembled and operated.

Onyx is a capable open-source toolkit, and that openness is a real advantage for some buyers. These are the places ZenSearch is built differently — governance, guardrails, performance, and a managed option with commercial support.

Governance on every action

ZenSearch

Each tool carries a risk tier (T0–T5). Consequential writes pause the run, enforce a pre-flight cost ceiling, and route an approval to the right human — in Slack, Teams, or on the web — with pause/resume and full audit logs.

Governance on every action

Onyx (Danswer)

Onyx focuses on retrieval and chat. It does not ship a per-action risk-tier policy engine, cross-surface human approvals, or pre-flight cost ceilings on agent writes — those would be built and operated separately.

Go-based performance

ZenSearch

ZenSearch's core services (API, search, vectorizer, collectors) are written in Go, delivering lower baseline memory consumption and better concurrency under load.

Go-based performance

Onyx (Danswer)

Onyx is built primarily in Python. While effective for prototyping, Python services typically require more resources and have higher latency under load.

Comprehensive AI guardrails

ZenSearch

Input and output guardrails including prompt injection detection, PII filtering, hallucination detection (lexical, semantic, hybrid), and toxicity filtering, with per-tenant configuration.

Comprehensive AI guardrails

Onyx (Danswer)

Onyx does not include built-in guardrails for prompt injection, PII detection, or hallucination scoring. Output validation would be implemented separately.

NL-to-SQL over your databases

ZenSearch

Ask questions in plain English against PostgreSQL, MySQL, ClickHouse, and SQL Server. Schema discovery, read-only execution, and query validation are built in.

NL-to-SQL over your databases

Onyx (Danswer)

Onyx does not support direct database querying. Database content must be ingested through file-based connectors or custom integrations.

A Closer Look

Open-source toolkit vs governed, supported coworker

Onyx's open-source codebase is a genuine strength — full source access, no vendor, community contributions. The trade-off is that you self-assemble and operate it. Here is that distinction side by side.

ZenSearch

  • Managed SaaS option with commercial support, or self-host on your own infrastructure
  • Governed agent actions out of the box — risk tiers T0–T5 and cross-surface approvals
  • Pre-flight cost ceilings and pause/resume on every consequential write
  • Built-in input + output guardrails (prompt injection, PII, hallucination)
  • Model Gateway with per-tenant usage tracking and per-team rate limits
  • Go core with lower baseline memory and better concurrency under load
  • Multi-tenant architecture with team-level isolation

Onyx (Danswer)

  • Fully open-source codebase with complete source access and no vendor lock-in
  • Community-supported — you operate, monitor, and update it yourself
  • Governance, approvals, and cost ceilings would be built and run separately
  • Guardrails for injection, PII, and hallucination are not included
  • LLM providers are called directly from application code
  • Built primarily in Python
  • Single-tenant only

Get Started

See the
difference.

Try ZenSearch in the live demo, or talk to our team about a deployment shaped to your environment.