Onyx (Danswer) vs ZenSearch: Open Source AI Search Compared
Onyx (formerly Danswer) is an open-source AI search assistant. ZenSearch is an enterprise AI search platform built in Go with a managed SaaS option. Here is how they compare on performance, features, deployment, and security.
Summary
Choose ZenSearch if you need:
- Production-grade Go performance with lower latency
- NL-to-SQL queries against enterprise databases
- Comprehensive AI guardrails and safety systems
- Multi-tenant architecture with team-level isolation
- Model Gateway with centralized cost tracking
- Free Lite self-host edition for evaluation
Choose Onyx if you need:
- Open-source codebase with community contributions
- Self-hosted deployment with full source access
- Python ecosystem compatibility for custom extensions
- No vendor dependency for core functionality
Search & AI Capabilities
| Feature | ZenSearch | Onyx |
|---|---|---|
Hybrid search (dense + sparse) | ||
Cross-encoder reranking | ||
Vector search | ||
Faceted search & filtering | ||
NL-to-SQL database queries Query PostgreSQL, MySQL, ClickHouse, SQL Server with natural language | ||
AI agents with tool calling | ||
Custom agent builder | Limited | |
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 | ||
Retrieval augmented generation | ||
Cited answers with sources | ||
Guardrails (hallucination, PII, injection) | ||
Answer confidence scoring | ||
Slack / Teams Surfaces | Slack, Teams, Chrome | Slack only |
AI Governance (Risk Tiers) | T0-T5 policy engine | Not available |
Cross-Surface Approvals | Slack, Teams, and web | Not available |
Scheduled Automations | Cron + event triggers | Not available |
Deployment & Architecture
| Feature | ZenSearch | Onyx |
|---|---|---|
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 | ||
Multi-tenant SaaS Onyx is single-tenant only |
Data Connectors
| Feature | ZenSearch | Onyx |
|---|---|---|
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
| Feature | ZenSearch | Onyx |
|---|---|---|
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
| Feature | ZenSearch | Onyx |
|---|---|---|
Primary language Go services for search, API, and vectorization deliver lower latency and memory usage | Go | Python |
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 | Qdrant | Vespa |
Embedding caching Redis-backed embedding cache reduces API costs on repeated content | ||
Incremental sync |
Where ZenSearch stands apart
Key areas where ZenSearch offers capabilities that Onyx does not.
Go-Based Performance
ZenSearchZenSearch's core services (API, search, vectorizer, collectors) are written in Go, delivering lower latency, reduced memory consumption, and better concurrency than Python-based alternatives.
Go-Based Performance
OnyxOnyx is built primarily in Python. While effective for prototyping, Python services typically require more resources and have higher latency under load.
NL-to-SQL Database Queries
ZenSearchQuery PostgreSQL, MySQL, ClickHouse, and SQL Server databases using natural language. Schema discovery, read-only execution, and query validation built in.
NL-to-SQL Database Queries
OnyxOnyx does not support direct database querying. Database content must be ingested through file-based connectors or custom integrations.
Comprehensive AI Guardrails
ZenSearchInput and output guardrails including prompt injection detection, PII filtering, hallucination detection (lexical, semantic, hybrid), and toxicity filtering. Per-tenant configuration.
Comprehensive AI Guardrails
OnyxOnyx does not include built-in guardrails for prompt injection, PII detection, or hallucination scoring. Output validation must be implemented separately.
Model Gateway with Usage Tracking
ZenSearchAll AI model calls route through a centralized Model Gateway with per-tenant usage tracking, rate limiting, cost monitoring, and provider switching — no code changes required.
Model Gateway with Usage Tracking
OnyxOnyx calls LLM providers directly from application code. Usage tracking and rate limiting must be implemented separately.
Multi-Tenant Architecture
ZenSearchZenSearch is designed from the ground up for multi-tenant deployment with team isolation, per-tenant rate limits, and shared infrastructure efficiency.
Multi-Tenant Architecture
OnyxOnyx is designed as a single-tenant application. Running multiple isolated tenants requires separate deployments, increasing operational complexity and cost.
Ready to try ZenSearch?
Evaluate the free Lite self-host edition or talk to our team about an enterprise deployment shaped to your environment.
See how ZenSearch compares to other enterprise search platforms.