Comparison
Apache Airflow is the open-source standard for code-first orchestration. Etlworks delivers built-in connectors, ETL, CDC, and EDI on top of orchestration — without writing or maintaining DAGs.
The verdict
Feature breakdown
| Capability | Etlworks | Airflow |
|---|---|---|
| Pricing & commercial | ||
| Starting price (monthly) | $300 | Free (OSS) / Astronomer or MWAA pricing |
| Pricing model | Fixed per tier | OSS or managed (Astronomer/MWAA/Cloud Composer) |
| Integration scope | ||
| Sources | 260+ | Provider operators (BYO code) |
| ETL capabilities | ETL, ELT, Reverse ETL, wildcard processing | Orchestrator only |
| API management | Full | |
| On-prem deployment | Self-host (OSS) | |
| Transformations | ||
| Visual mapping | drag-and-drop designer with live preview | transformation is your code |
| Scripting languages | SQL, JavaScript, Python, XSLT, shell | Python, plus whatever you import |
| Nested and hierarchical data | JSON, XML, Avro, Parquet — read, write, normalize, flatten by dragging | if you write it |
| Warehouse pushdown (ELT) | transform before load or in the warehouse, same engine | Partial — if your code does it |
| Reusable logic | macros, templates, and 3,900+ prebuilt flow templates | Python modules and packages |
| Lookups and enrichment | Lookup Builder for cross-source lookups | Partial — your code |
| Data validation | validation rules with per-step error handling | Partial — libraries such as Great Expectations |
| Orchestration & workflow | ||
| Scheduling | Cron expressions and fixed intervals, with per-schedule parameters | Cron and interval, defined in Python DAGs |
| Event-driven triggers | HTTP listeners and webhooks, message queues, file and email events | Partial — sensors and the REST API, not a listener endpoint |
| Continuous execution | looping schedules for CDC and queue consumers | Partial — short-interval schedules and sensors |
| Visual workflow builder | Composer canvas, 200+ flow types | DAGs are Python; the UI displays them |
| Nested workflows | nested flows with conditional and looped steps | sub-DAGs, task groups, branching |
| Run external tools | shell and SSH scripts, CLI, JavaScript, Python, SQL, HTTP calls | Bash, SSH, Docker, and Kubernetes operators |
| Parallel execution | overlapping schedules run as independent, separately cancellable instances | parallel tasks across workers |
| Retries and error handling | per-step exception handling with notifications | per-task retries, callbacks, SLAs |
| Run monitoring | per-schedule status, run history, automatic Flow Findings reports | run history, Gantt and graph views |
| CDC & Streaming | ||
| CDC engine | Debezium-compatible, built-in (no Kafka required) | orchestrator only — CDC requires external operators |
| Database CDC sources | MySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others | Via custom operators / external tools (Debezium, etc.) |
| Streaming queues | Kafka, EventHubs, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Via custom operators |
| IoT brokers | MQTT brokers | |
| Real-time replication | Log-based CDC, full, incremental | batch orchestration |
| Change tracking modes | Log-based, trigger-based, timestamp/high-watermark | Per-DAG implementation |
| Developer experience | ||
| REST API | full API for flows, connections, schedules, and runs | |
| CLI | full CLI with built-in SQL | the primary interface |
| MCP server | built-in — connect Cursor, Claude, or ChatGPT to your instance | |
| Client libraries | Python, Bash, and PowerShell clients | Python-native, plus provider packages |
| Version control | built-in — automatic history, diff, and revert on every artifact | git, because pipelines are code |
| Embeddable / white-label | ||
| Compliance & security | ||
| SOC 2 Type 2 | audited; report under NDA, SOC 3 public | your deployment, your audit |
| HIPAA | supported with a BAA | your responsibility |
| GDPR / DPA | compliant, DPA available | no vendor to sign a DPA with |
| SSO and MFA | SAML SSO, optional 2FA, JWT stateless auth | Partial — whatever you configure |
| Role and artifact-level access | six roles plus tag-based scoping of flows, connections, and schedules | Partial — basic RBAC, no artifact scoping |
| Encryption and data handling | TLS in transit, encrypted at rest, customer-managed PGP, SSH tunnels, IP allowlisting; rows are not persisted by default | Partial — whatever you configure |
| Audit logging | admin actions logged, access logs monitored | Partial — application logs only |
| Security testing | monthly vulnerability and penetration scans, static analysis blocking every build, periodic third-party audits | community-reported CVEs |
| Gen AI | ||
| AI agent | Built-in agent (Simba) — builds and edits flows from chat | orchestrator — AI is added externally |
| Agent capabilities | Reads metadata, reads/samples data, writes JS & SQL, schedules, deploys, monitors | |
| Natural-language flow building | ‘Vibe-build’ — create flows by describing what you want | |
| AI-driven mapping | Auto-suggests source-to-destination mappings | |
| Built-in analytics | Agent runs analysis on flow data and pipeline behavior | |
| Chat across product | Same agent context on every screen | |
| CLI for agent | Full CLI access for run/deploy/monitor/manage | Full CLI for the orchestrator (not an AI agent) |
| Trains on customer data | Never | N/A |