Comparison
AWS Glue is the natural choice if you live entirely inside AWS. Etlworks gives you the same data integration capabilities across multi-cloud, on-prem, and hybrid, with visual flows instead of PySpark.
The verdict
Feature breakdown
| Capability | Etlworks | AWS Glue |
|---|---|---|
| Pricing & commercial | ||
| Starting price (monthly) | $300 | Pay per DPU-hour (~$0.44/DPU-hr) |
| Pricing model | Fixed per tier | Consumption (DPU-hours) |
| Integration scope | ||
| Sources | 270+ | AWS-centric + JDBC |
| ETL capabilities | ETL, ELT, Reverse ETL, wildcard processing | Spark-based ETL |
| API management | Full | |
| On-prem deployment | ||
| Transformations | ||
| Visual mapping | drag-and-drop designer with live preview | Glue Studio visual editor |
| Scripting languages | SQL, JavaScript, Python, XSLT, shell | PySpark, Scala, Python |
| Nested and hierarchical data | JSON, XML, Avro, Parquet: read, write, normalize, flatten by dragging | Partial: passes JSON through, unpacking happens downstream |
| Warehouse pushdown (ELT) | transform before load or in the warehouse, same engine | Partial: Spark, or push into Redshift |
| dbt integration | dbt Core as a native flow type, Git-pinned, plus dbt Platform job triggers | no native dbt task |
| Reusable logic | macros, templates, and 3,900+ prebuilt flow templates | jobs and shared libraries |
| Lookups and enrichment | Lookup Builder for cross-source lookups | |
| Data validation | validation rules with per-step error handling | |
| Orchestration & workflow | ||
| Scheduling | Cron expressions and fixed intervals, with per-schedule parameters | Cron via Glue triggers or EventBridge |
| Event-driven triggers | HTTP listeners and webhooks, message queues, file and email events | EventBridge and S3 events |
| Continuous execution | looping schedules for CDC and queue consumers | Partial: streaming ETL jobs |
| Visual workflow builder | Composer canvas, 200+ flow types | Glue Studio and workflows |
| Nested workflows | nested flows with conditional and looped steps | Partial: workflows and triggers, Step Functions for real branching |
| Run external tools | shell and SSH scripts, CLI, JavaScript, Python, SQL, HTTP calls | Partial: Python shell jobs; other AWS services via Step Functions |
| Parallel execution | overlapping schedules run as independent, separately cancellable instances | parallel jobs and DPUs |
| Retries and error handling | per-step exception handling with notifications | job retries, DLQ patterns |
| Run monitoring | per-schedule status, run history, automatic Flow Findings reports | CloudWatch metrics and logs |
| Lineage and audit trail | run-level lineage (trigger, flow, dbt commit, outcome) plus a filterable audit trail | Partial: job run history; lineage needs DataZone or SageMaker Catalog |
| CDC & Streaming | ||
| CDC engine | Debezium-compatible, built-in (no Kafka required) | AWS DMS (separate service, often paired) |
| Database CDC sources | MySQL, Postgres, SQL Server, Oracle, MongoDB, DB2, others | Via DMS, broad coverage |
| Streaming queues | Kafka, EventHubs, Kinesis, SQS, PubSub, ActiveMQ, RabbitMQ | Kinesis, MSK (Kafka) |
| IoT brokers | MQTT brokers | |
| Real-time replication | Log-based CDC, full, incremental | Streaming jobs (Spark Streaming) |
| Change tracking modes | Log-based, trigger-based, timestamp/high-watermark | Log-based via DMS |
| Developer experience | ||
| REST API | full API for flows, connections, schedules, and runs | cloud API |
| CLI | full CLI with built-in SQL | cloud CLI |
| MCP server | built-in: connect Cursor, Claude, or ChatGPT to your instance | |
| Client libraries | Python, Bash, and PowerShell clients | cloud SDKs in many languages |
| Version control | built-in: automatic history, diff, and revert on every artifact | Partial: infrastructure-as-code, not artifact history |
| Embeddable / white-label | ||
| Compliance & security | ||
| SOC 2 Type 2 | audited; report under NDA, SOC 3 public | plus ISO 27001, PCI, FedRAMP |
| HIPAA | supported with a BAA | covered by the cloud BAA |
| GDPR / DPA | compliant, DPA available | |
| SSO and MFA | SAML SSO, optional 2FA, JWT stateless auth | cloud IAM and directory integration |
| Role and artifact-level access | six roles plus tag-based scoping of flows, connections, and schedules | fine-grained IAM policies |
| Encryption and data handling | TLS in transit, encrypted at rest, customer-managed PGP, SSH tunnels, IP allowlisting; rows are not persisted by default | platform KMS, customer-managed keys |
| Audit logging | admin actions logged, access logs monitored | cloud-native audit trail |
| Security testing | monthly vulnerability and penetration scans, static analysis blocking every build, periodic third-party audits | continuous, platform-wide |
| Gen AI | ||
| AI agent | Built-in agent (Simba) that builds and edits flows from chat | use Bedrock externally |
| Agent capabilities | Reads metadata, reads/samples data, writes JS & SQL, schedules, deploys, monitors | Code generation suggestions in Glue Studio |
| Natural-language flow building | ‘Vibe-build’, create flows by describing what you want | Partial: Q in Glue (preview, AWS-context only) |
| AI-driven mapping | Auto-suggests source-to-destination mappings | Partial: schema discovery via crawlers |
| 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 | |
| Trains on customer data | Never | Not by default |