Comparison

Etlworks vs n8n

n8n is self-hostable workflow automation with genuinely good AI-agent tooling. Etlworks is built for data volume instead — log-based CDC, bulk loads, warehouses, and EDI — with an AI agent that builds the pipelines.

The verdict

When each tool fits.

When Etlworks fits better

  • You are moving tables and files, not triggering app actions
  • You need log-based CDC from production databases
  • You need EDI (X12, EDIFACT, HL7) processing
  • You need continuous schedules and parallel runs, not per-execution billing
  • You want warehouse-grade bulk loading and wildcard processing

Where they’re equal

  • Self-hosted deployment behind your own firewall
  • An AI agent built into the product
  • Visual building with the option to drop into code
  • Event-driven triggers, webhooks, and scheduled runs
  • Running shell commands and scripts from a workflow

When n8n fits better

  • Your work is app-to-app automation rather than data movement
  • You are building AI agents with custom tools and memory
  • You want a free self-hosted tier with unlimited executions
  • You want a very large community node library
  • Per-execution pricing suits a low-volume workload

Feature breakdown

Side by side.

Capability Etlworks n8n
Pricing & commercial
Starting price (monthly)$300Free (Community, self-hosted) / Cloud from EUR 24
Pricing modelFixed per tierPer execution; self-hosted Business at $800/mo
Cost transparencyHigh — flat rateMedium — execution counts are easy to underestimate
Vendor lock-inMonthly or annual, no contractSource-available; self-host with no vendor
Integration scope
Sources260+500+ app integrations
DestinationsWarehouses, databases, SaaS, NoSQL, files, APIs, queues, IoT, emailSame node library
ETL capabilitiesETL, ELT, Reverse ETL, wildcard processingPartial — per-item workflow logic, not bulk ETL
API managementFullHTTP nodes and webhooks
EDI processingX12, EDIFACT, HL7, FHIR
On-prem deploymentself-host, Docker
EmbeddablePartial — embed licence
Transformations
Visual mappingdrag-and-drop designer with live previewPartial — field mapping per step
Scripting languagesSQL, JavaScript, Python, XSLT, shellJavaScript or Python in code steps
Nested and hierarchical dataJSON, XML, Avro, Parquet — read, write, normalize, flatten by draggingPartial — JSON per item, no bulk flattening
Warehouse pushdown (ELT)transform before load or in the warehouse, same engine
Reusable logicmacros, templates, and 3,900+ prebuilt flow templatesreusable sub-workflows
Lookups and enrichmentLookup Builder for cross-source lookupsPartial — lookup via extra API calls
Data validationvalidation rules with per-step error handlingPartial — conditional branches
Orchestration & workflow
SchedulingCron expressions and fixed intervals, with per-schedule parametersInterval and cron-style schedules
Event-driven triggersHTTP listeners and webhooks, message queues, file and email eventswebhooks and app triggers — the primary model
Continuous executionlooping schedules for CDC and queue consumersPartial — polling and webhook triggers
Visual workflow builderComposer canvas, 200+ flow typesthe core of the product
Nested workflowsnested flows with conditional and looped stepssub-workflows
Run external toolsshell and SSH scripts, CLI, JavaScript, Python, SQL, HTTP callsExecute Command node when self-hosted, plus Code nodes
Parallel executionoverlapping schedules run as independent, separately cancellable instancesPartial — concurrency depends on your own infrastructure
Retries and error handlingper-step exception handling with notificationsper-step retry and error branches
Run monitoringper-schedule status, run history, automatic Flow Findings reportsexecution history
CDC & Streaming
CDC engineDebezium-compatible, built-in (no Kafka required)
Database CDC sourcesMySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others
Streaming queuesKafka, EventHubs, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQKafka, RabbitMQ, AMQP, MQTT
IoT brokersMQTT brokersMQTT node
Real-time replicationLog-based CDC, full, incrementalpolling and webhook triggers
Change tracking modesLog-based, trigger-based, timestamp/high-watermarkPolling, webhooks
Developer experience
REST APIfull API for flows, connections, schedules, and runs
CLIfull CLI with built-in SQLn8n CLI
MCP serverbuilt-in — connect Cursor, Claude, or ChatGPT to your instance
Client librariesPython, Bash, and PowerShell clientsPartial — community SDKs
Version controlbuilt-in — automatic history, diff, and revert on every artifactPartial — git integration on enterprise plans
Embeddable / white-label
Compliance & security
SOC 2 Type 2audited; report under NDA, SOC 3 publicPartial — cloud and enterprise, not community
HIPAAsupported with a BAAPartial — higher tiers only
GDPR / DPAcompliant, DPA available
SSO and MFASAML SSO, optional 2FA, JWT stateless authPartial — SSO on enterprise plans
Role and artifact-level accesssix roles plus tag-based scoping of flows, connections, and schedulesPartial — role-based, no artifact-level scoping
Encryption and data handlingTLS in transit, encrypted at rest, customer-managed PGP, SSH tunnels, IP allowlisting; rows are not persisted by defaultself-hosted keeps data in your network
Audit loggingadmin actions logged, access logs monitoredPartial — enterprise tier
Security testingmonthly vulnerability and penetration scans, static analysis blocking every build, periodic third-party auditsvendor-managed, details on request
Gen AI
AI agentBuilt-in agent (Simba) — builds and edits flows from chatAI agent nodes with tools and memory, self-hostable
Agent capabilitiesReads metadata, reads/samples data, writes JS & SQL, schedules, deploys, monitorsBuilds and runs agent workflows against your nodes
Natural-language flow building‘Vibe-build’ — create flows by describing what you wantAI workflow builder
AI-driven mappingAuto-suggests source-to-destination mappings
Built-in analyticsAgent runs analysis on flow data and pipeline behavior
Chat across productSame agent context on every screenPartial — assistant inside the editor
CLI for agentFull CLI access for run/deploy/monitor/managen8n CLI
Trains on customer dataNeverNo when self-hosted